JP4910990B2 - Leather shape data generation device, leather shape data generation method, and leather shape data generation program - Google Patents

Description

  The present invention relates to a computer graphics for expressing the uneven shape of the leather surface, a leather shape data generating device for generating data used for forming the uneven shape of the surface when manufacturing synthetic leather, etc., leather shape The present invention relates to a technical field of a data generation method and a leather shape data generation program.

  Since the fine irregularities (leather wrinkles) such as pores and grooves formed on the leather surface produce a natural texture, synthetic leather and other materials with such irregularities are It is used as a surface decoration material for various industrial products such as automobile interior materials and handbag materials. CG (Computer Graphics) images have been used as image images that are the basis for forming irregularities on the surface of leather on such materials. In this CG image production, the fine irregularities on the surface of leather are reproduced. Is required.

  Conventionally, leather shape generation methods in CG image production are roughly classified into two methods.

  First, the first method is a method in which a pattern of natural leather is photographed and the image is regarded as a leather shape and reproduced. Specifically, after extracting a part of the photo, joining the extracted images side by side, generating a large leather pattern image, and applying seamless processing to make the joints of the image inconspicuous, texture images and By pasting the bump mapping image and the displacement image in a three-dimensional shape, the texture of the leather is simulated.

  Next, the second method is to generate a fine uneven shape of leather with an algorithm alone, convert it into an image, paste it into a three-dimensional shape, and reproduce the texture and texture of the leather in a pseudo manner Procedural way. This method is proposed in Non-Patent Documents 1 and 2, for example.

  In Non-Patent Document 1, a planar shape of a surface is generated by Voronoi division, a fluctuation is given to the divided polygon, and then a stretch conversion based on directionality is given to the polygon, The processing is recursively performed on each divided polygon to form a hierarchical structure, and the cross-sectional shape of the surface is expressed by a Pezier curve, and the control point of this Pezier curve is changed to an arc shape to give a roundness, By these, a method for expressing a skin mound, a skin groove or the like is disclosed.

In Non-Patent Document 2, a cluster of several cells is used as a leather cell at the macro level, this leather cell is regarded as a particle, and the potential of the field for controlling the orientation of the particle is defined. Combine the repulsive force due to the interstitial force and the potential, simulate the growth of leather cells by the Runge-Kutta method, perform rounding operation and sweep on the base shape of the generated leather cells, and uneven the surface of the base shape by the metaball As a result, a method of expressing a cuticle, a skin groove, or the like is disclosed.
Ishii, 3 others, “A method for expressing the texture of the skin focusing on the fine shape of the surface”, Transactions of Information Processing Society of Japan, Information Processing Society of Japan, 1991, Vol. 32, No. 5, p.645- 654 Miyata and 3 others, “Generating Leather Texture Using Particles and Metaballs”, Research Report, Information Processing Society of Japan, 2006, Vol. 119, p. 13-18

  However, in the first method described above, since the illumination environment at the time of taking a picture is different from the illumination environment in a virtual three-dimensional space at the time of image production by CG, the leather represented by the created texture image or the like May be different from the texture of the leather that was filmed. In the first method, the extracted leather images are stitched together to generate a large leather image. At this time, the uneven surface pattern of the photographed leather surface appears repeatedly, and the leather surface It could not be said that the shape of was naturally expressed.

  On the other hand, the above-described Non-Patent Documents 1 and 2 disclose a method for expressing a skin hill, a skin groove, and the like, but do not disclose anything about the expression of pores formed on the leather surface.

  For these reasons, conventionally, the arrangement pattern of pores and the like could not be expressed naturally.

  The present invention has been made in view of the above problems, and a leather shape data generation device and a leather shape data generation method capable of naturally reproducing the arrangement pattern of pores formed on the surface of natural leather or the like It is another object of the present invention to provide a leather shape data generation program.

  In order to solve the above-mentioned problem, the invention according to claim 1 is characterized in that the leather shape data acquisition means for acquiring leather shape data indicating the uneven shape of the leather surface, and the leather based on the acquired leather shape data. Based on the pore position specifying means for specifying the position of the pores on the surface, and identifying the dense pores based on the position of the specified pores, and classifying the dense pores into the same group, A pore group specifying means for specifying a pore group on the leather surface, a position of each pore in the specified pore group, and a probability variable of the probability that pores are arranged in the pore group, using the position as a random variable Pore distribution data generating means for generating pore distribution data indicating the distribution, and specifying the pore group adjacent to the specified pore group; Pore group distribution data generation for generating pore group distribution data indicating the distribution of the probability that the pore group adjacent to the pore group is arranged using a relative position from the position on the leather surface of the pore group as a random variable Means, and leather shape data generating means for generating new leather shape data in accordance with the generated pore distribution data and the generated pore group distribution data.

  According to this invention, the pore group according to the pore group distribution data indicating the probability distribution that the pore group adjacent to the pore group is arranged on the leather surface and the pore distribution data indicating the probability distribution that the pore is arranged in the pore group. Since the new leather shape data is generated by arranging the pores and pores, the generated leather shape data naturally reproduces the arrangement pattern of pore groups and the arrangement pattern of pores formed on the surface of natural leather etc. can do.

  The invention according to claim 2 is an approximation formula for approximating a probability distribution indicated by the pore group distribution data based on the generated pore group distribution data in the leather shape data generation device according to claim 1. A parameter generating unit that generates parameters used for the storage, a storage unit that stores the generated parameter and the generated pore distribution data in association with each other, and a plurality of the parameters stored in the storage unit And the leather shape data generation means generates the pore group distribution data based on the generated synthesis parameter and the approximate expression, and the plurality of parameters. In accordance with at least one of the plurality of pore distribution data corresponding to and the pore group distribution data , And generates the new leather shape data.

  According to this invention, it is possible to easily generate new leather shape data having an intermediate characteristic of the arrangement pattern characteristics of pore groups on the surface of a plurality of leathers.

  According to a third aspect of the present invention, in the leather shape data generating device according to the first or second aspect, the leather shape data includes a height of the surface at a position corresponding to the element on the leather surface. It is the data expressed by the two-dimensional arrangement | sequence which shows.

  According to this invention, pore distribution data and pore group distribution data can be easily generated.

  The invention according to claim 4 specifies a leather shape data acquisition step for acquiring leather shape data indicating the uneven shape of the leather surface, and specifies a position of a pore on the leather surface based on the acquired leather shape data. Based on the pore position identifying step and the position of the identified pores, the pores on the leather surface are identified by identifying the dense pores and classifying the dense pores into the same group. Pore group identification step, and the position of each pore in the identified pore group is identified, and pore distribution data indicating the distribution of the probability that the pore is arranged in the pore group is generated using the position as a random variable A pore distribution data generation step for identifying the pore group adjacent to the identified pore group, and the leather of the pore group A pore group distribution data generating step for generating pore group distribution data indicating a distribution of the probability that the pore group adjacent to the pore group is arranged, using the relative position from the position on the surface as a random variable; A leather shape data generating step for generating new leather shape data according to the pore distribution data and the generated pore group distribution data.

  According to a fifth aspect of the present invention, a computer is caused to function as the leather shape data generating device according to any one of the first to third aspects.

  According to the present invention, the arrangement pattern of pore groups and the arrangement pattern of pores formed on the surface of natural leather or the like can be naturally reproduced by newly generated leather shape data.

[1. Basic principle]
The best mode for carrying out the present invention will be described below with reference to the drawings. Prior to that, the basic principle of the embodiment will be described with reference to FIG.

  Fig.1 (a), (b) and (c) is a figure which shows the example of the uneven | corrugated pattern of the surface of the natural leather which has a pore, FIG.1 (d) expands a part of Fig.1 (a). FIG. In each figure, the spots expressed in black indicate pores, and the altitude in the normal direction with respect to the leather surface is lower than the portion expressed in white. That is, the spots expressed in black are concave portions on the leather surface. The concave shape of the pores is usually formed gently in many cases, but in FIG. 1, for convenience of explanation, the altitude is expressed by binary values of black and white.

  Here, in the example of FIG. 1 (d), it can be seen that three pores are densely formed and a group is formed by the dense pores (in the figure, each group is represented by a dashed ellipse). (Enclosed). Since the distance from the pores in one group to the pores in the other group is usually longer than the distance between the pores in the group, when looking at the leather surface from a distance, this group itself looks like one pore. May appear. Hereinafter, this group is referred to as a composite follicle (an example of a pore group).

  As shown in FIG. 1 (d), it can be seen that the number and arrangement of pores in the composite hair follicle are similar between the composite hair follicles. That is, the arrangement pattern of the pores in the composite hair follicle can be seen. Moreover, as shown to FIG. 1 (a), (b) and (c), also about the arrangement | positioning of a composite hair follicle, a pattern is seen for every leather. For example, in the case of FIG. 1A, when the upper direction on the paper is an angle of 0, it seems that the composite hair follicles are connected in the direction of about 50 degrees to the right.

  In the embodiment described below, the arrangement pattern of the composite follicle and the arrangement pattern of the pores in the composite follicle are read from the real leather, and new leather shape data is generated according to these arrangement patterns. It has become.

  Specifically, for each composite hair follicle, the composite hair follicle adjacent to the composite hair follicle is specified, and the relative position (two-dimensional) of the composite hair follicle adjacent to the composite hair follicle is set with the composite hair follicle point as the origin. And the relative probability of this relative position as a random variable, the probability distribution of the appearance of adjacent complex hair follicles, that is, the probability that adjacent complex hair follicles will be arranged at what position A composite follicle distribution diagram (an example of pore group distribution data) is generated, and this is used as a composite hair follicle arrangement pattern.

  Further, the position of each pore in the composite hair follicle is obtained, and the position in the composite hair follicle is used as a random variable, and the probability distribution of each hair follicle, that is, each pore in the composite hair follicle is within the composite hair follicle. A pore distribution diagram (an example of pore distribution data) indicating at what position and with what probability is generated, and this is used as a pore arrangement pattern.

  In the embodiment, the composite hair follicles are randomly arranged with the appearance probability distribution indicated by the composite follicle distribution map as a weight, and the pores are randomly assigned with the appearance probability distribution indicated by the pore distribution map as a weight within each composite follicle. Will continue to arrange. As a result, leather shape data indicating the uneven shape of the leather surface is generated.

  Of course, the leather shape data generated in this way is data that captures the characteristics of the arrangement pattern of the composite hair follicle in the real leather and the arrangement pattern of the pores in the composite hair follicle. In addition, the uneven shape of the leather surface can be naturally expressed regardless of the size of the image of the newly generated leather shape data.

  In the embodiment, leather shape data is generated by multiplying a plurality of leather features. At this time, since the feature of the uneven shape on the leather surface particularly depends on the arrangement pattern of the composite hair follicle, in the embodiment, the arrangement pattern of the composite hair follicle of each leather is multiplied.

  Specifically, an approximation formula of the appearance probability distribution shown in the composite hair follicle distribution map is prepared in advance, and the parameters used for the approximation formula (hereinafter referred to as “feature parameters”) are respectively leathers to which the features are multiplied. Is calculated and stored in advance. Then, the stored feature parameters are synthesized, and using the synthesized feature parameters, an appearance probability distribution is calculated by an approximate expression, and a new composite hair follicle distribution diagram is generated.

By following this new composite follicle distribution map, it is possible to generate leather shape data that combines multiple leather features.
[2. Embodiment]
Next, an embodiment when the present invention is applied to a leather shape data generation device will be described.
[2.1 Structure and function overview of leather shape data generator]
First, with reference to FIG. 2, the structure and outline | summary function of the leather shape data generation apparatus which concern on this embodiment are demonstrated.

  FIG. 2 is a diagram illustrating a schematic configuration example of the leather shape data generation device S according to the present embodiment.

  As shown in FIG. 2, the leather shape data generation device S according to the present embodiment includes a control unit 10 including a CPU (Central Processing Unit) 17, a ROM (Read Only Memory) 18, a RAM (Random Access Memory) 19, and the like. And a storage unit 20 (for example, a hard disk drive) as an example of a storage means for storing various programs (for example, leather shape generation data program) and data. The control unit 10 includes a three-dimensional input device 1 as an example of a shape measuring device, an external input device 2 (for example, a keyboard and a mouse), and a display device 3 (for example, a CRT (Cathode Ray Tube) display, a liquid crystal display, and the like. ). As the leather shape data generation device S, for example, a personal computer can be applied.

  The three-dimensional input device 1 measures the three-dimensional coordinates of the leather surface at a pitch of several μm to several tens of μm, generates the leather shape data of the leather surface that is the measurement object, and the leather shape data is converted into the leather shape data. The data is output to the data generation device.

  The format of the leather shape data is a so-called height field. Specifically, in this format, the height of the leather surface at each coordinate on a plane passing through this origin and substantially parallel to the leather surface is defined as a two-dimensional array with a certain position on the leather surface as the origin. It is a representation. This altitude is expressed by, for example, 256 levels from 0 to 255, where 0 is black, 255 is white, and 1 to 254 is expressed in gray according to each value. , And can be expressed as a grayscale two-dimensional image.

  As the three-dimensional input device 1, for example, a non-contact type measurement device using a laser (for example, a three-dimensional scanner) or a contact type measurement device using a needle can be applied.

  As the three-dimensional input device 1, a two-dimensional scanner can be applied. A two-dimensional scanner is originally a device that measures the gray value of an object from the reflectance on a two-dimensional plane, but when measuring a fine uneven shape such as the shape of a leather surface, the inclination of this uneven shape is measured. Since the reflectance is changed by the above, the uneven shape of the object can be captured from this change.

  When a two-dimensional scanner is applied, the system can be configured at a lower cost than a three-dimensional scanner or the like, but the measurement accuracy is lowered.

  The control unit 10 is an example of a three-dimensional input device control unit 11, a leather shape data acquisition unit, a pore position identification unit, a pore group identification unit, a pore distribution data generation unit, a pore group distribution data generation unit, and a parameter generation unit. The configuration includes a feature extraction unit 12, a feature synthesis unit 13 as an example of a synthesis unit, and a leather shape generation unit 14 as an example of a leather shape data generation unit.

  Then, the CPU reads out and executes various programs stored in the ROM and the storage unit 20 so that the control unit 10 controls each part of the leather shape data generation device S, and the three-dimensional input device control unit 11, the feature extraction The unit 12, the feature synthesis unit 13, and the leather shape generation unit 14 function as the above-described means.

  Various programs may be acquired from a server device or the like via a network, or may be recorded on a recording medium such as a CD-ROM and read via a disk drive or the like. good.

  The three-dimensional input device control unit 11 controls the operation of the three-dimensional input device 1 and registers the leather shape data output from the three-dimensional input device 1 in the leather shape database 21.

  The feature extraction unit 12 reads the leather shape data registered in the leather shape database 21, generates a composite hair follicle distribution diagram and a pore distribution diagram based on the leather shape data, and generates the generated composite hair follicle distribution. The feature parameters are calculated based on the figure, and the pore distribution diagram and the feature parameters are registered in the feature parameter database 22.

  The feature synthesizer 13 reads a plurality of feature parameters registered in the feature parameter database 22, synthesizes these feature parameters, generates a new feature parameter, and registers the feature parameter in the feature parameter database 22. It has become. At this time, the feature synthesis unit 13 registers a part or all of the pore distribution map corresponding to each of the read feature parameters in the feature parameter database 22 in association with the newly generated feature parameter. ing. Note that the feature parameter newly generated by the synthesis process by the feature synthesis unit 13 is referred to as a “synthesis feature parameter”.

  The leather shape generation unit 14 generates new leather shape data based on the feature parameters registered in the feature parameter database 22 and the pore distribution map, and registers the leather shape data in the leather shape database 23. Yes.

  The specific processing contents of the three-dimensional input device control unit 11 to the leather shape generation unit 14 will be described later.

  In the storage unit 20, a leather shape database 21, a feature parameter database 22, and a leather shape database 23 are constructed.

  In the leather shape database 21, leather shape data output from the three-dimensional input device 1 is registered in association with the identification information.

  In the feature parameter database 22, feature parameters and pore distribution diagrams generated by the control unit 10 are registered in association with the identification information.

In the leather shape database 23, the leather shape data generated by the control unit 10 is registered in association with the identification information. The leather shape data registered in the leather shape database 23 is used as a texture image, a bump image, a displacement mapping image, or the like. The leather shape database 21 and the leather shape database 23 may be integrated, and the leather shape data may be managed by one database.
[2.2 Operation of leather shape data generator]
Next, the operation of the leather shape data generation device S will be described.
[2.2.1 Overview of leather shape data extraction / synthesis / generation processing]
First, leather shape data extraction / synthesis / generation processing, which is an overall process in the leather shape data generation apparatus S, will be described with reference to FIGS. 3 and 4. FIG. 3 is a flowchart showing a processing example of leather shape data extraction / synthesis / generation processing of the leather shape data generation device S according to the present embodiment. FIG. 4 is a diagram illustrating an example of the leather shape data represented by a gray scale image.

  First, when an operator inputs the leather shape data by operating the external input device 2, the three-dimensional input device control unit 11 controls the three-dimensional input device 1 as shown in FIG. Then, the uneven shape of the leather surface is measured, the leather shape data is input from the three-dimensional input device 1, new identification information is assigned, and the leather shape data is registered in the leather shape database 21 in association with the identification information. (Step S1). At this time, the three-dimensional input device 1 measures the altitude (for example, expressed in 256 steps) at a pitch of 90 μm for a 9 cm × 9 cm region on the leather surface, and the leather shape data is obtained as a height field of 1001 × 1001. Generate.

  FIG. 4 is an example in which this leather shape data is expressed as a gray scale image. In FIG. 4, for the sake of convenience, the image size is indicated by 60 pitches × 60 pitches, and the altitude is indicated by six levels.

  Next, the feature quantity extraction unit 12 generates feature parameters and pore distribution diagrams based on the leather shape data registered in the leather shape database 21 by executing a feature extraction process described later, and features them. Register in the parameter database 22 (step S2).

  Next, the control unit 10 determines whether or not to synthesize feature parameters based on the selection operation of the external input device 2 by the operator (step S3). Here, in the case of synthesizing feature parameters (step S3: YES), the feature synthesizer 13 executes feature synthesize processing described later to obtain feature parameter data registered in the feature parameter database 22. The combined feature parameters are generated and registered in the feature parameter database 22 (step S4). Thereafter, the control unit 10 proceeds to step S5. On the other hand, when the feature parameters are not synthesized (step S3: NO), the process proceeds to step S5.

  In step S5, the leather shape generation unit 14 executes a leather shape generation process, which will be described later, so that new leather shape data is created based on the feature parameters registered in the feature parameter database 22 and the pore distribution diagram. Is registered in the leather shape database 23. At this time, if it is determined in step S3 that the feature parameters are to be synthesized (step S3: YES), the leather shape generation unit 14 performs processing using the synthesized feature parameters and determines not to synthesize the feature parameters. If so (step S3: NO), processing is performed using normal feature parameters.

When this process ends, the control unit 10 ends the leather shape data extraction / synthesis / generation process.
[2.2.2 Feature extraction processing]
Next, the feature extraction process in step S2 will be described with reference to FIGS.

  FIG. 5 is a flowchart showing a processing example of feature extraction processing of the leather shape data generation device S according to the present embodiment. FIG. 6 is a diagram illustrating an example in which the positions of the pore candidates are displayed superimposed on the gray scale image of the leather shape data. FIG. 7 is a graph showing a distribution of the number of appearances of pore candidates at each altitude. FIGS. 8A and 8B are diagrams illustrating an example of a method for identifying pores from pore candidates. Moreover, FIG. 9 is a figure which shows an example at the time of displaying a pore point superimposed on the gray scale image of leather shape data. FIG. 10 is a diagram showing an example in which the predicted position, range, and adjacency relationship of the composite hair follicle are displayed superimposed on the gray scale image of the leather shape data.

  FIG. 11 is a diagram showing a graph of the distribution of the number of appearance of adjacent pore points for each distance between adjacent pore points. Moreover, FIG. 12 is a figure which shows an example at the time of displaying the specified compound hair follicle point superimposed on the gray scale image of leather shape data. FIG. 13 is a diagram illustrating an example of a pore distribution diagram. Moreover, FIG. 14 is a figure which shows an example of a composite hair follicle distribution map. FIG. 15 is obtained by converting the composite follicle distribution chart shown in FIG. 14 into a new coordinate system with the distance in the radial direction from the composite hair follicle point as the horizontal axis and the angle in the radial direction as the vertical axis. It is a figure which shows an example of a figure.

  FIG. 16 is a diagram showing an example in which the centers of gravity of adjacent compound hair follicle points are displayed superimposed on the compound hair follicle distribution map. FIG. 17 is a diagram illustrating an example in which an elliptical shape estimated from the center of gravity of adjacent composite hair follicle points is displayed superimposed on the composite hair follicle distribution diagram. FIG. 18 is a diagram showing an example of a diagram obtained by modifying the diagram shown in FIG. 17 with the distance in the radial direction from the center of the compound hair follicle as the horizontal axis and the angle in the radial direction as the vertical axis. . FIG. 19 is a diagram illustrating an example of a method for obtaining the deviation σ1 and the deviation σ2 from the probability density function in which adjacent complex hair follicles appear in the radial direction from the complex hair follicle point. FIG. 20 is a diagram showing an example of a graph of the deviation σ1 and the deviation σ2 and a graph of a sine wave approximated to each.

  When leather shape data to be used for processing is designated by identification information or the like by the operator operating the external input device 2, the feature extraction unit 12 converts the designated leather shape data into leather as shown in FIG. It reads out from the shape database and extracts the position of the pore point from this leather shape data (step S11). Here, a pore point is a point which shows the position where the pore is arrange | positioned, and let the center of a pore be a pore point in this embodiment.

  Specifically, the feature extraction unit 12 first extracts the minimum value of the gray value (altitude) from the gray scale image of the leather shape data, and uses the coordinates of this minimum value as the position of the pore point candidate. More specifically, the feature extraction unit 12 compares the gray value of the pixel of interest on the gray scale image with the gray value of each pixel in the surrounding n × n (n is a natural number). When the gray value is the minimum value, this target pixel is set as a candidate position for the pore point. The feature extraction unit 12 performs this process for all pixels on the grayscale image. FIG. 6 shows the result.

  The number of pixels 1 at this time can be arbitrarily determined, but it is desirable that the number of pixels corresponds to the vertical or horizontal length of the pores. Therefore, for example, a grayscale image of leather shape data May be displayed on the display device 3, and the operator may determine the average size of the pores from this image and set the number of pixels l.

  When the feature extraction unit 12 extracts the positions of pore point candidates, the feature extraction unit 12 deletes unnecessary candidates. That is, the feature extraction unit 12 excludes pore candidates from those that may be depressions that are not pores.

  FIG. 7 is a graph showing the distribution of the number of occurrences of pore candidates at each altitude. In this figure, there are two distributions such as a normal distribution (the distribution on the left side of the page is P1, the distribution on the right side). Can be seen as P2). Here, since the height of the pores is considered to be lower than the height of the dents other than the pores, the distribution of the pores is considered to be the distribution P1, and the distribution of the dents other than the pores is considered to be the distribution P2 (that is, the distribution P1 is the distribution P2). Less altitude). Therefore, by setting a certain altitude between the distribution P1 and the distribution P2 as a threshold (maximum altitude of pore points), the distribution P1 and the distribution P2 are divided by this threshold, and the distribution on the right side is deleted from the threshold. The position can be specified.

  Specifically, since the distribution P1 is considered to be a substantially symmetrical distribution, the feature extraction unit 12 first obtains the maximum value of the distribution P1 as shown in FIG. Identify the distribution on the left (middle thick line in FIG. 8 (a)) with the altitude at which the value is obtained as the boundary, and invert the left distribution with the line passing through the altitude at which the maximum value is obtained and perpendicular to the x axis as the axis of symmetry Thus, as shown in FIG. 8B, a line-symmetric distribution is obtained (the thick line in FIG. 8B). Then, the feature extraction unit 12 obtains the area of this distribution, and the ratio of the area of this distribution and the area from 0 to the threshold of the area is, for example, 100: 99 (this ratio is arbitrarily determined) The threshold is calculated so that this ratio is obtained.

  In some cases, three or more distributions may appear, or two distributions may overlap, and the distributions may not be clearly distinguished at first glance. A threshold can be determined.

  The feature extraction unit 12 deletes pore point candidates at altitudes higher than the threshold value thus obtained, and extracts the positions of the pore points. FIG. 9 shows the result.

  Next, the feature extraction unit 12 extracts the complex hair follicles by classifying the dense pores into the same composite hair follicle based on the extracted pore positions, and calculates the position of the composite hair follicle point. (Step S12). Here, the composite hair follicle point is a point indicating the position where the composite hair follicle is arranged, and in this embodiment, the emphasis is placed on the pore point in the composite hair follicle.

  Here, first, a method for extracting a composite hair follicle will be described. Since the composite hair follicle is formed by a plurality of follicles being densely packed, the distance between the pores in the composite hair follicle is shorter than the distance from each pore of the composite hair follicle to the pores of the other composite hair follicles. It is considered a thing. Therefore, it can be estimated that a pore belonging to a certain composite follicle is located within a circle having a predetermined radius centered on the composite follicle point. Therefore, it is only necessary to obtain this radius and extract a composite hair follicle based on this radius.

  In FIG. 10, the range of the composite hair follicle is represented as a circle having a radius T around the composite hair follicle point, and the Delaunay side when the Delaunay division is performed with the composite hair follicle point as the Delaunay point is adjacent. It is represented as a connecting line between complex follicle points. From this figure, it can be inferred that the radius T is about ½ of the average distance between adjacent composite hair follicles represented by this connecting line.

  However, the distance between the composite hair follicle points cannot be calculated unless the composite hair follicle is first extracted and the position of the composite hair follicle point is calculated. Therefore, in the present embodiment, the radius T is calculated based on the distance between adjacent pore points.

  Specifically, the feature extraction unit 12 generates a Delaunay diagram using the extracted pore points as Delaunay points, and recognizes that the pore points that are Delaunay points directly connected by Delaunay sides are adjacent to each other. Then, the feature extraction unit 12 calculates the distance between all adjacent pore points, normalizes this distance to an integer, and counts the number of appearances for each distance. A graph of the number of appearances at this time is shown in FIG.

  If the distance between the compound hair follicle points is calculated from the distribution shown in this graph and the radius T, which is the threshold value, is obtained from this, the threshold value T varies each time the measurement range is changed in the three-dimensional input device 1. May end up. Therefore, when it is assumed that the area of the distribution that exceeds the threshold T (the portion filled with black in the figure) is 5% of the area of the entire distribution, the threshold T is the composite hair. Since it was found when the inventors of the present invention tried to calculate the threshold value T for a certain leather, it was found that it was close to ½ of the average distance between the bags. The threshold value T is calculated so that the area of the distribution at T is 95% of the area of the entire distribution. Note that the method for calculating the threshold T is not limited to this.

  After calculating the threshold value T, the feature extraction unit 12 performs pore grouping based on the threshold value T. Specifically, the feature extraction unit 12 groups pore points whose mutual distance is equal to or less than the threshold T, and starts this process from the pore points whose mutual distance is the shortest, and exceeds the threshold T. End with. At this time, when three or more pore points belong to one composite follicle, the already-grouped pore points and the ungrouped pore points are combined into one group. Although necessary, the feature extraction unit 12 performs grouping based on the distance between the center of gravity of pore points that are already grouped and the pore points that are not grouped. That is, if the distance is equal to or less than the threshold value T, the feature extraction unit 12 collects pore points that have already been grouped and pore points that have not been grouped into one group. By doing in this way, the pore point located within the radius T centering on a composite hair follicle point can be grouped in the form close | similar to the premise that it belongs to this composite hair follicle.

  After completing the grouping, the feature extraction unit 12 recognizes each group as a composite hair follicle, calculates the position of the composite hair follicle point, and retains this value. FIG. 12 shows the result.

  Next, the feature extraction unit 12 generates a pore distribution map based on the positional relationship between the pores in the composite hair follicle (step S13).

  Specifically, the feature extraction unit 12 obtains the relative position (two-dimensional coordinate) of the pore point in the composite hair follicle with the composite hair follicle point as the origin, and performs this process on all composite hair follicles. And the feature extraction part 12 counts the appearance number of a pore point for every relative position from a composite hair follicle point. The feature extraction unit 12 generates a two-dimensional image representing the appearance probability thus determined as a pore distribution map, and registers this in the feature parameter database 22 in association with the identification information of the leather shape data.

  FIG. 13 is a diagram when a pore distribution map is displayed with the pixel position with the highest appearance probability being white and the position with the lowest appearance probability being black, and the position of each pixel on the pore distribution map is a composite It corresponds to the relative position from the hair follicle point. In the same figure, the appearance probability is shown in six stages for convenience.

  Next, the feature extraction unit 12 generates a composite hair follicle distribution map (step S14).

  Specifically, the feature extraction unit 12 generates a Delaunay diagram using the calculated composite hair follicle point as a Delaunay point, and recognizes that the composite hair follicle points that are Delaunay points directly connected by Delaunay sides are adjacent to each other. .

  Next, the feature extraction unit 12 obtains the relative position (two-dimensional coordinates) of the compound hair follicle point adjacent to the compound hair follicle point of interest as the origin, normalizes this position to an integer, and performs this processing for all the compound hair follicle points. Perform on the hair follicle point. Then, the feature extraction unit 12 counts the number of appearances of adjacent compound hair follicle points for each relative position from the compound hair follicle point of interest. The feature extraction unit 12 generates a two-dimensional image representing the appearance probability thus obtained as a complex hair follicle distribution map.

  FIG. 14 is a diagram when a composite hair follicle distribution map is displayed with the pixel position having the highest appearance probability being white and the position having the lowest appearance probability being black, and each pixel on the composite hair follicle distribution map is displayed. The position corresponds to the relative position from the compound follicle point of interest. In the same figure, the appearance probability is shown in six stages for convenience.

  Next, the feature extraction unit 12 calculates feature parameters based on the generated composite follicle distribution map (step S15).

  Specifically, as shown in FIG. 14, the adjacent complex hair follicle points are distributed on an ellipse centered on the target complex hair follicle point. Find the formula.

  More specifically, the feature extraction unit 12 calculates an angle θ based on a predetermined direction from the composite hair follicle point (for example, an upward direction on the paper in FIG. 14) from the composite hair follicle point from the y axis, Is converted into a new coordinate system with the distance in the radial direction as the x-axis. The composite follicle distribution map converted in this way is shown in FIG.

  Next, the feature extraction unit 12 calculates the center of gravity of the composite hair follicle point at this angle from the probability distribution of adjacent composite hair follicle points at each angle based on the new coordinate system. FIG. 16 is a diagram in which the center of gravity calculated in this way is displayed superimposed on the composite hair follicle distribution diagram.

  The feature extraction unit 12 estimates an elliptical shape represented by the following expression (1) from the center of gravity group of the composite hair follicle using the least square method.

In the above formula (1), β is the inclination of the ellipse, and a and b are the major radius and minor radius of the ellipse. FIG. 17 is a diagram in which the ellipses thus estimated are displayed superimposed on the composite hair follicle distribution map.

  Next, the feature extraction unit 12 converts the estimated ellipse into the new coordinate system described above. FIG. 18 shows the result.

  Next, the feature extraction unit 12 cuts out the composite hair follicle distribution map and ellipse converted into a new coordinate system for each angle (see the upper part of FIG. 19), and approximates the probability distribution for each angle with a predetermined probability density function. To do. This probability density function f (x) can be expressed by the following equation (2).

here,

It is. In the above equation, σ (x) is a standard deviation at a distance x in the radial direction from the compound follicle point of interest, e is a natural logarithm, and μ is a radius at an estimated elliptical angle θ. . Further, the distribution of FIG. 19 is regarded as separate normal distributions on the left and right with the radius μ as a boundary, σ1 is the deviation of the distribution diagram of FIG. 19 when 0 ≦ x ≦ μ, and σ2 is the distribution of FIG. 19 when x> μ. This is the deviation of the distribution chart (see the lower graph in FIG. 19). Also, σ ₁ and σ ₂ satisfy σ ₁ <σ ₂ .

From the above equation, it can be seen that the probability distribution f (x) for each angle is obtained by the radius μ, the deviation σ ₁ , and the deviation σ ₂ . At this time, the graph of the deviation σ ₁ and the deviation σ ₂ with the angle θ as the x axis and the deviation as the y axis is a line graph as shown in FIG. Here, since the adjacent complex hair follicle points are distributed on an ellipse centered on the compound hair follicle point of interest, a _{graph of} deviation σ _{1 and a graph} of deviation σ ₂ corresponding to this elliptical shape, Since each is close to a sine wave, the feature extraction unit 12 estimates the sine wave S (θ) by the following equation (1) using the least square method.

In the above formula, d is an amplitude, ψ is a phase at the origin, 2 is a period, and f is an average value of deviations. The two sine wave graphs shown in FIG. 20 are a sine wave that approximates the deviation σ ₁ and a sine wave that approximates the deviation σ ₂ .

As described above, the information shown by the composite hair follicle distribution map, that is, the probability distribution in which the composite hair follicle adjacent to the target composite hair follicle appears on the basis of the target composite hair follicle point is expressed by the equations (1) to (1). It can be approximated by (4) and equation (6). That is, the composite follicle distribution map can be approximately obtained from the inclination β, the major radius a, the minor radius b, the radius μ, and the deviation σ ₁ and deviation σ ₂ for each angle. Here, the radius μ is not necessary because it can be calculated from the elliptical expression (1). Since the deviation σ ₁ and the deviation σ _{2 for} each angle can be approximated by the equation (6), the deviation σ ₁ is the amplitude d ₁ , the phase ψ ₁ , the average value f ₁ of the deviation, The deviation σ ₂ can be expressed by the amplitude d ₂ , the phase ψ ₂ , and the average value f ₂ of the deviation.

Therefore, the composite follicle distribution diagram is represented by slope β, major radius a, minor radius b, amplitude d ₁ , phase ψ ₁ , average deviation f ₁ , amplitude d ₂ , phase ψ ₂ , and average deviation f ₂ . Therefore, the feature extraction unit 12 uses these nine parameters as feature parameters and registers them in the feature parameter database 22 in association with the identification information of the leather shape data. As a result, the pore distribution map and the feature parameter are associated with each other.

When this process ends, the feature extraction unit 12 ends the feature extraction process.
[2.2.3 Feature synthesis processing]
Next, the feature synthesis process in step S4 will be described.

  When two or more leathers to be synthesized are designated by identification information or the like by operating the external input device 2 by the operator, the feature synthesis unit 13 sets the corresponding pore distribution map and feature parameters for the designated leather. A synthesized feature parameter is generated by reading out from the feature parameter database 22 and synthesizing the feature parameter for each parameter. As a synthesis method at this time, for example, linear interpolation or a weighted average may be obtained.

  Next, the feature synthesizer 13 assigns new identification information, associates the generated synthesized feature parameter and all or part of the read pore distribution map with this identification information in the feature parameter database 22. sign up.

  Strictly speaking, although not a synthesis, a synthesized feature parameter may be generated by adding noise to a feature parameter of one leather without synthesizing a plurality of feature parameters.

When this process is completed, the feature synthesis unit ends the feature synthesis process.
[2.2.4 Leather shape generation processing]
Next, the leather shape generation process in step S5 will be described with reference to FIGS.

  FIG. 21 is a flowchart showing a processing example of leather shape generation processing of the leather shape data generation device S according to the present embodiment. Fig. 22 (a) is a diagram showing an example of a probability distribution graph of a composite hair follicle at a certain y coordinate, and Fig. 22 (b) is a graph obtained by first differentiating the graph shown in Fig. 22 (a). FIG. 22C is a diagram showing a partial arrangement of gradient data as a vector.

  Moreover, Fig.23 (a) and (b) are figures which show an example of the production | generation method of a composite hair follicle non-arrangement area | region. FIGS. 24A to 24D are diagrams showing an example of a method for arranging the compound hair follicle points. FIGS. 25A to 25D are diagrams showing an example of the shape of the pores. Moreover, Fig.26 (a) and (b) are figures which show an example of a mode that a pore is formed.

  When the operator operates the external input device 2 and a feature parameter (normal feature parameter or composite feature parameter) to be used for processing is designated by identification information or the like, the leather shape generation unit 14 is as shown in FIG. Then, the designated feature parameter is read from the feature parameter database 22, and the original composite hair follicle distribution map is restored using this feature parameter and the equations (1) to (4) and (6) ( Step S21).

  Next, the leather shape generation unit 14 determines the number of composite hair follicles to be finally arranged (step S22).

  Specifically, the leather shape generation unit 14 calculates the number of composite hair follicles per unit area from the number of composite hair follicles specified in the feature extraction process, and based on the image size of the newly generated leather shape data. To determine the number of composite hair follicles to be arranged. For example, when the number of composite hair follicles per 100 pixels × 100 pixels is 80 and the size of the leather shape data to be generated is 1000 pixels × 1000 pixels, the number of composite hair follicles to be arranged = (1000 ÷ 100 ) × (1000 ÷ 100) × 80 = 8000. Note that the method of determining the number is not limited to this. For example, the operator may specify the number, and when the read feature parameter is a combined feature parameter, it corresponds to the feature parameter before combining. Then, the average value of the number of composite hair follicles specified in the feature extraction process may be used.

  Next, the leather shape generation unit 14 generates gradient data based on the restored original composite follicle distribution map (step S23). Here, the gradient data is a two-dimensional array of two-dimensional vectors calculated by firstly differentiating the composite hair follicle distribution diagram in the x-axis direction and the y-axis direction (see FIG. 22C). This gradient data is used when determining the movement direction when moving the complex hair follicle position in step S29 described later.

  Specifically, for example, when the appearance probability of an adjacent complex follicle point at coordinates (x, y) is F (x, y), the leather shape generation unit 14 is F (x, y) −F ( x-1, y) is obtained and pseudo first-order differentiation is performed, and this is set as a vector in the x-axis direction of coordinates (x, y). Further, the leather shape generation unit 14 calculates F (x, y) −F (x, y−1) and sets this as a vector in the y-axis direction of the coordinates (x, y). And the leather shape production | generation part 14 performs this process about all the coordinates. The sum of the vector in the x-axis direction and the vector in the y-axis direction of the coordinate (x, y) calculated in this way becomes a two-dimensional vector at the coordinate (x, y).

  FIG. 22A is a graph of the probability distribution of the composite hair follicle obtained by cutting the composite hair follicle distribution map at the y coordinate = y1. FIG. 22B is a graph of gradient data (only in the x-axis direction) at y-coordinate = y1. FIG. 22C is a diagram showing a part of the gradient data as a vector. In these figures, the origin is the position of the compound hair follicle point of interest.

  Next, the leather shape generation unit 14 generates a composite hair follicle non-arrangement region diagram based on the restored original composite hair follicle distribution map (step S24). Here, the composite hair follicle non-arrangement region diagram is an image data indicating a region where an adjacent composite hair follicle point does not exist in the composite hair follicle distribution diagram inside the distribution in which the adjacent composite hair follicle point appears. It is. This composite hair follicle non-arrangement region diagram is a diagram showing a region in which the placement of composite hair follicle points is prohibited when the composite hair follicle is temporarily placed in the process of step S25 described later.

  Specifically, the leather shape generation unit 14 starts a search from a complex hair follicle point of interest based on the original complex hair follicle distribution map as shown in FIG. As shown in the drawing, pixels having an appearance probability of adjacent composite hair follicle points of 0 are grouped to make an area where no adjacent composite hair follicle point exists, and a composite hair follicle non-arrangement region diagram is generated. In FIG. 23B, r is a composite hair follicle non-arrangement region.

  Next, the leather shape generation unit 14 sets a drawing area having a specified image size on, for example, a RAM, and stores the original composite follicle distribution map, the number of composite follicle points to be temporarily arranged, and the composite follicle non-arrangement. Based on the area diagram, the compound hair follicle point is temporarily arranged in this drawing area (step S25).

  Specifically, the leather shape generation unit 14 first determines the number of composite follicle points to be temporarily arranged. More specifically, the number larger than the final number is set as the temporary number. For example, it may be obtained by multiplying the number to be finally arranged by a predetermined coefficient, or may be set by an operator.

  Next, the leather shape generation unit 14 arranges the first composite hair follicle point at an arbitrary position on the drawing area of the designated image size, and the composite hair follicle non-arrangement area on the drawing area with this as the center. Draw with overlapping figures. And the leather shape production | generation part 14 superimposes the original composite hair follicle distribution map centering on the 1st composite hair follicle point, and uses the appearance probability distribution which this superimposed composite hair follicle distribution map shows as a weight 2 at random. Place the th compound hair follicle point. FIG. 24A shows the result, in which a1 is the first compound hair follicle point, a2 is the second compound hair follicle point, and p1 is the compound hair of a1. FIG.

  Next, the leather shape generation unit 14 draws the composite hair follicle non-arrangement region drawing on the drawing region with the second composite hair follicle point as the center. FIG. 24B shows the result. Then, the leather shape generation unit 14 superimposes the original composite follicle distribution map around the first composite follicle point, and randomly assigns the appearance probability distribution indicated by the superimposed composite follicle distribution map to 3 Place the th compound hair follicle point. At this time, the leather shape generation unit 14 arranges the composite hair follicle point so that the composite hair follicle point is not arranged in the region indicated by the composite hair follicle non-arrangement region diagram. FIG. 24 (c) shows the result. In FIG. 24, a3 is the third compound hair follicle point. Next, the leather shape generation unit 14 draws the composite hair follicle non-arrangement region drawing on the drawing region with the third composite hair follicle point as the center (see FIG. 24D).

  In this way, the leather shape generation unit 14 sequentially arranges the composite hair follicle points, and when the adjacent composite hair follicle point cannot be arranged with respect to the first composite hair follicle point, the second composite hair follicle point is obtained. For the hair follicle point and the third composite hair follicle point, the composite hair follicle point is arranged in the same manner as in the case of the first composite hair follicle point. Then, the leather shape generation unit 14 deletes the composite hair follicle non-arrangement region diagram from the drawing region when the number of the composite hair follicle points arranged reaches the number of the composite hair follicle points to be temporarily placed. The temporary arrangement is terminated.

  Since the composite hair follicle points on the drawing area are arranged according to the original composite hair follicle distribution map, it can be said that this layout pattern shows the characteristics of the layout pattern indicated by the composite hair follicle distribution map. Therefore, you may transfer to the arrangement | positioning of the pore after step S31 mentioned later by making the position of the composite hair follicle point arrange | positioned here into a final position. However, in this embodiment, in order to make it closer to the characteristics of the arrangement pattern indicated by the composite follicle distribution map, the composite hair follicle points described below are deleted and moved.

  When finishing the temporary arrangement of the composite hair follicle points, the leather shape generation unit 14 generates a temporary composite hair follicle distribution map based on the positions of the composite hair follicle points temporarily placed in the drawing region (step S26). The method for generating the composite hair follicle distribution map is the same as the method described in step S14 of the feature extraction process.

  Next, the leather shape generation unit 14 ranks each composite follicle point temporarily arranged (step S27). This rank indicates the value of the composite follicle point, and the lower this value, the higher the value.

  Specifically, the leather shape generation unit 14 calculates, for each coordinate, the difference between the appearance probability indicated by the original composite hair follicle distribution map and the appearance probability indicated by the temporary composite hair follicle distribution map, and the absolute value of this difference. Is the rank at that coordinate. And the leather shape production | generation part 14 adjoins the rank corresponding to the position which made the noted compound hair follicle point the origin about each compound hair follicle point (specified by Delaunay division) adjacent to the noticed compound hair follicle point. Add as the rank of the compound hair follicle point. And the leather shape production | generation part 14 calculates the rank of each compound hair follicle point by performing the same process about all the compound hair follicle points.

  Next, the leather shape generation unit 14 deletes the compound hair follicle point from the drawing area based on the calculated rank (step S28).

  Specifically, the leather shape generation unit 14 deletes the complex hair follicle points having higher ranks, and terminates the deletion of the composite hair follicle points when the number of deletions reaches a predetermined number. The number of deletions is arbitrary. For example, the number of composite hair follicles to be finally arranged may be ½ of the difference between the number of composite hair follicles temporarily arranged before deletion, or the operator may May be set.

  Next, the leather shape generation unit 14 moves the composite hair follicle point temporarily arranged on the drawing area based on the rank and the gradient data (step S29).

Specifically, the leather shape generation unit 14 first identifies a composite hair follicle point adjacent to the target composite hair follicle point by Delaunay division. Then, the leather shape generation section 14, a movement vector V _i of each composite follicle point is calculated by the following equation (7). Note that i is an integer that satisfies the number of complex hair follicle points that are currently 1 ≦ i ≦ temporarily arranged.

In the above formula (7), m _i is the number of composite hair follicle points adjacent to the composite hair follicle point i, and v _ij is a composite hair corresponding to the composite hair follicle point ij adjacent to the composite hair follicle point i. This is a movement vector of the wrapping point i, and k _ij is a coefficient.

  here,

It is. In the above formula (8), x _ij and y _ij are the x coordinate and y coordinate of the composite follicle point i with the composite follicle point ij adjacent to the composite follicle point i as the origin, and F ₁ (x _ij , y _ij ) is an appearance probability at the coordinates (x _ij , y _ij ) on the original composite hair follicle distribution map, and F ₂ (x _ij , y _ij ) is on the temporary composite hair follicle distribution map. It is the appearance probability at the coordinates (x _ij , y _ij ).

In the above equation (9), vf ₁ (x _ij , y _ij ) is gradient data (vector) generated from the original composite follicle distribution map corresponding to the coordinates (x _ij , y _ij ). .

In the above equation (10), vf ₂ (x _ij , y _ij ) is gradient data generated from the temporary composite hair follicle distribution map corresponding to the coordinates (x _ij , y _ij ). This gradient data is generated in the same manner as the method described in step S23.

That is, the leather shape generation unit 14 generates the gradient data generated from the original composite follicle distribution map corresponding to the relative position of the composite follicle point i from the composite follicle point ij and the temporary composite follicle distribution map. Calculate the difference vector, convert the difference vector into a unit vector, add it to the gradient data obtained from the original composite follicle distribution map, further normalize it to the unit vector, On the other hand, the difference (the difference in the relative position of the composite hair follicle point i from the composite hair follicle point ij) between the appearance probability shown in the original composite hair follicle distribution map and the appearance probability shown in the temporary composite hair follicle distribution map is By multiplying, the movement vector of the compound hair follicle point i when the compound hair follicle point ij is regarded as the target compound hair follicle point is calculated. Then, the leather shape generation unit 14 moves the movement vector of the composite hair follicle point i corresponding to the composite hair follicle point i1, the movement vector of the composite hair follicle point i corresponding to the composite hair follicle point i2, and so on. by summing the movement vector of the composite hair follicles points i corresponding to _i, and calculates a movement vector V _i of the composite hair follicle point i. The leather shape production | generation part 14 performs such a process about all the composite hair follicle points.

At this time, the normalized movement vector V _ij / | V _ij | indicates the moving direction of the compound hair follicle point i when the compound hair follicle point ij is the target compound hair follicle point, and the coefficient k _ij is The amount of movement of the compound hair follicle point i and whether to reverse the moving direction are shown.

  After calculating the final movement vector, the leather shape generation unit 14 moves all the composite follicle points according to each final movement vector.

  Next, the leather shape generation unit 14 determines whether or not the number of composite hair follicle points currently temporarily arranged is equal to or less than the final number determined in step S22 (step S30). When the number is not less than the final number (step S30: NO), the process proceeds to step S26. That is, the leather shape generation unit 14 performs deletion and movement of the composite hair follicle point shown in steps S26 to S29 until the number of composite hair follicle points is equal to or less than the final number.

  When the number of composite follicle points is equal to or less than the final number (step S30: YES), the leather shape generation unit 14 determines the pore points based on the positions of the arranged composite follicle points and the pore distribution diagram. Are arranged (step S31).

  Specifically, the leather shape generation unit 14 first reads the pore distribution map corresponding to the feature parameter read in step S21 from the feature parameter database 22. And the leather shape production | generation part 14 superimposes a pore distribution map centering on the arrange | positioned composite follicle point, and arrange | positions a pore point at random using the appearance probability distribution which this superimposed pore distribution map shows as a weight. .

  At this time, the number of pores arranged corresponding to one composite follicle point may be obtained, for example, by dividing the number of composite follicles from the number of pores specified in the feature extraction process. A probability distribution of pores to be arranged for each composite follicle point may be obtained and randomly determined for each composite follicle point according to this distribution. Further, when the composite hair follicle points are arranged based on the composite feature parameter, for example, an average value of the number of pores specified in the feature extraction process corresponding to each of the feature parameters before composition, and the composite hair follicle The average value of the number of the hair follicles may be obtained, and the average value of the number of the composite follicles may be divided from the average value of the number of the pores. Data necessary for calculating the number of pores to be arranged is registered in the feature parameter database 22 in association with the feature parameter. The number of pores arranged for one composite follicle point may be set by the operator.

  Furthermore, when a composite follicle point is arranged based on the composite feature parameter, a plurality of pore distribution diagrams may be associated with the composite feature parameter and registered in the feature parameter database 22, It is necessary to select a pore distribution map used for arrangement of pore points. In this case, for example, a pore distribution map designated by the operator may be used, or may be determined at random for each composite follicle point.

  After finishing the arrangement of the pore points, the leather shape generation unit 14 forms pores for the respective pore points on the drawing area (step S32).

  For example, as shown in FIGS. 25A to 25D, a plurality of pore shape data indicating the concave shape of the pores are registered in the storage unit 20 as height fields. When one of the registered pore shape data is selected by the operator operating the external input device 2, the leather shape generation unit 14 selects the selected pore shape data around the pore point. Is drawn in the drawing area. When drawing of pore shape data is completed for all pore points, the data indicating the uneven shape drawn in this drawing area becomes the leather shape data indicating the uneven shape of the new leather surface. FIG. 26A is a part of a drawing area where pore points are arranged, and FIG. 26B is a drawing in which the pore shape data shown in FIG. It is a part of the area, and the data on this drawing area becomes new leather shape data.

  For example, the feature of the pore shape may be extracted in the feature extraction process, the pore shape data may be generated based on the feature, and the pore may be formed using the pore shape data.

  After finishing the pore formation, the leather shape generation unit 14 newly assigns identification information, registers the generated new leather shape data in the leather shape database in association with the identification information, and performs leather shape generation processing. End.

  As described above, according to the present embodiment, the feature extraction unit 12 reads the leather shape data generated by measuring the uneven shape of the leather surface by the three-dimensional input device 1 from the leather shape database 21, and this By identifying the position of pore points based on the leather shape data, identifying the dense pores based on the identified pore point positions, and classifying the dense pores into the same group Identifying the composite hair follicle, specifying the position of the pore point in the composite hair follicle, and using the position as a random variable, generating a pore distribution map showing the probability distribution of the pore point in the composite hair follicle Identifying the composite hair follicle adjacent to the composite hair follicle, and using the relative position from the position of the composite hair follicle on the leather surface as a random variable, the distribution of the probability of the composite hair follicle adjacent to the composite hair follicle being placed It is adapted to generate a composite to the hair follicle distribution chart.

  Further, the feature extraction unit 12 generates feature parameters used in the equations (1) to (4) and (6) for approximating the probability distribution indicated by the generated composite hair follicle distribution map, The generated pore distribution map is associated with and registered in the feature parameter database 22. Then, the leather shape generation unit 14 restores the original composite follicle distribution map based on the feature parameters and the expressions (1) to (4) and (6), and the pore distribution map corresponding to the feature parameters is restored. According to the composite follicle distribution map, new leather shape data is generated.

  Therefore, the arrangement pattern of the composite hair follicle and the arrangement pattern of the pores formed on the surface of natural leather or the like can be naturally reproduced by the new leather shape data.

  In addition, the feature synthesis unit 13 generates a synthesized feature parameter by synthesizing a plurality of feature parameters registered in the feature parameter database 22, and the leather shape generation unit 14 generates a plurality of pore distributions corresponding to the plurality of feature parameters. Since new leather shape data is generated according to at least one of the figures and the synthetic feature parameter, a new leather having a feature obtained by multiplying a plurality of leather surface pores and a composite follicle arrangement pattern Shape data can be easily generated.

  In addition, since the leather shape data is expressed by a height field indicating the height of the surface at a position corresponding to the element on the leather surface, the pore distribution chart and the composite follicle distribution chart can be easily generated. be able to.

  In the present embodiment, since features of a plurality of leathers may be multiplied, a feature parameter is generated from the composite follicle distribution map generated by the feature extraction process, and this feature parameter is synthesized. However, when it is not necessary to combine features of a plurality of leathers, it is not necessary to generate feature parameters. In this case, the pore distribution map generated by the feature extraction process and the composite follicle distribution map are associated with each other and stored in the storage unit 20 or the like, and a new one is created according to the pore distribution map and the composite follicle distribution map. The leather shape data may be generated.

  Further, in the present embodiment, the leather shape data is expressed by the height field, but the method of expressing the leather shape data is not limited to this.

  In the present embodiment, the acquisition source of the leather shape data by the feature extraction unit 12 is the leather shape database 21, but is not limited to this, and for example, the leather shape output from the three-dimensional input device 1. Data may be acquired via the three-dimensional input device control unit 11.

(A), (b) and (c) is a figure which shows the example of the uneven | corrugated pattern of the surface of the natural leather which has a pore, (d) is the figure which expanded a part of (a). It is a figure showing an example of outline composition of leather shape data generation device S concerning this embodiment. It is a flowchart which shows the process example of the leather shape data extraction / synthesis | combination production | generation process of the leather shape data generation apparatus S which concerns on this embodiment. It is a figure which shows an example at the time of expressing leather shape data with a gray scale image. It is a flowchart which shows the process example of the feature extraction process of the leather shape data generation apparatus S which concerns on this embodiment. It is a figure which shows an example at the time of displaying the position of a pore candidate superimposed on the gray scale image of leather shape data. It is a figure which shows the graph of the distribution of the appearance number of the candidate of a pore in every altitude. (A) And (b) is a figure which shows an example of the method of specifying a pore from the candidate of a pore. It is a figure which shows an example at the time of displaying a pore point superimposed on the gray scale image of leather shape data. It is a figure which shows an example at the time of overlaying and displaying the position, range, and adjacency relationship which were estimated of the composite hair follicle on the gray scale image of leather shape data. It is a figure which shows the graph of distribution of the appearance number of the adjacent pore point for every distance between adjacent pore points. It is a figure which shows an example at the time of displaying the specified compound hair follicle point superimposed on the gray scale image of leather shape data. It is a figure which shows an example of a pore distribution map. It is a figure which shows an example of a composite hair follicle distribution map. The figure which shows an example of the figure obtained by transforming the composite hair follicle distribution map shown in FIG. 14 into a new coordinate system with the distance in the radial direction from the composite follicle point as the horizontal axis and the angle in the radial direction as the vertical axis It is. It is a figure which shows an example at the time of displaying the gravity center of an adjacent composite hair follicle point superimposed on a composite hair follicle distribution map. It is a figure which shows an example at the time of displaying the ellipse shape estimated from the gravity center of the adjacent composite hair follicle point on a composite hair follicle distribution map. It is a figure which shows an example of the figure obtained by transforming the figure shown in FIG. 17 by setting the distance in the radial direction from the center of the composite hair follicle as the horizontal axis and the angle in the radial direction as the vertical axis. It is a figure which shows an example of the method of calculating | requiring deviation (sigma) 1 and deviation (sigma) 2 from the probability density function in which the adjacent composite hair follicle appears in the radial direction from a composite hair follicle point. It is a figure which shows an example of the graph of deviation (sigma) 1 and deviation (sigma) 2, and the graph of the sine wave approximated to each. It is a flowchart which shows the process example of the leather shape production | generation process of the leather shape data production | generation apparatus S which concerns on this embodiment. (A) is a figure which shows an example of the graph of the probability distribution of the composite hair follicle in a certain y coordinate, (b) is a figure which shows an example of the graph which carried out the primary differentiation of the graph shown to (a), (C) is the figure which represented the partial arrangement | sequence of gradient data with the vector. (A) And (b) is a figure which shows an example of the production | generation method of a composite hair follicle non-arrangement area | region. (A) thru | or (d) is a figure which shows an example of the arrangement | positioning method of a composite hair follicle point. (A) thru | or (d) is a figure which shows an example of the shape of a pore. (A) And (b) is a figure which shows an example of a mode that a pore is formed.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 3D input device 2 External input device 3 Display apparatus 10 Control part 11 3D input device control part 12 Feature extraction part 13 Feature composition part 14 Leather shape production | generation part 20 Storage part 21, 23 Leather shape database 22 Feature parameter database S Leather Shape data generator

Claims (5)

Leather shape data acquisition means for acquiring leather shape data indicating the uneven shape of the leather surface;
Based on the acquired leather shape data, pore position specifying means for specifying the position of the pores on the leather surface;
A pore group specifying means for identifying a pore group on the leather surface by identifying dense pores based on the identified pore positions and classifying the dense pores into the same group; ,
Pore distribution data generating means for specifying the position of each pore in the specified pore group, and generating pore distribution data indicating the distribution of the probability that the pore is arranged in the pore group, using the position as a random variable; ,
Probability that the pore group adjacent to the pore group is arranged by specifying the pore group adjacent to the specified pore group and using the relative position from the position on the leather surface of the pore group as a random variable Pore group distribution data generating means for generating pore group distribution data indicating the distribution of
Leather shape data generating means for generating new leather shape data according to the generated pore distribution data and the generated pore group distribution data;
A leather shape data generating device comprising: In the leather shape data generation device according to claim 1,
Based on the generated pore group distribution data, parameter generation means for generating parameters used in an approximate expression for approximating the probability distribution indicated by the pore group distribution data;
Storage means for storing the generated parameter and the generated pore distribution data in association with each other;
A synthesis unit that generates a synthesis parameter by synthesizing the plurality of parameters stored in the storage unit;
The leather shape data generation means generates the pore group distribution data based on the generated composite parameter and the approximate expression, and at least one of the plurality of pore distribution data corresponding to the plurality of parameters. According to the pore group distribution data, the new leather shape data is generated. In the leather shape data generation device according to claim 1 or 2,
The leather shape data generating apparatus according to claim 1, wherein the leather shape data is data expressed in a two-dimensional array in which each element indicates a height of the surface at a position corresponding to the element on the leather surface. Leather shape data acquisition process for acquiring leather shape data indicating the uneven shape of the leather surface;
Based on the acquired leather shape data, a pore position specifying step for specifying the position of the pores on the leather surface;
A pore group identification step of identifying a pore group on the leather surface by identifying dense pores based on the position of the identified pores and classifying the dense pores into the same group; ,
A pore distribution data generation step of identifying the position of each pore in the identified pore group, and generating pore distribution data indicating the distribution of the probability that the pore is arranged in the pore group using the position as a random variable; ,
Probability that the pore group adjacent to the pore group is arranged by specifying the pore group adjacent to the specified pore group and using the relative position from the position on the leather surface of the pore group as a random variable Pore group distribution data generation step for generating pore group distribution data indicating the distribution of
A leather shape data generating step for generating new leather shape data according to the generated pore distribution data and the generated pore group distribution data;
A leather shape data generation method comprising:   A leather shape data generation program for causing a computer to function as the leather shape data generation device according to any one of claims 1 to 3.