WO2019001164A1

WO2019001164A1 - Optical filter concentricity measurement method and terminal device

Info

Publication number: WO2019001164A1
Application number: PCT/CN2018/087482
Authority: WO
Inventors: 孔庆杰
Original assignee: 精锐视觉智能科技（深圳）有限公司
Priority date: 2017-06-26
Filing date: 2018-05-18
Publication date: 2019-01-03
Also published as: CN107356213B; CN107356213A

Abstract

The present solution is applied in the technical field of industrial inspection and provides an optical filter concentricity measurement method and a terminal device. The method comprises: obtaining an initial image comprising an optical filter; extracting a target area image in the initial image as an image to be tested, the target area image being an image corresponding to an outer outline of the optical filter in the initial image; performing denoising on the image to be tested; and respectively calculating positions of central points of a first outline and a second outline in the denoised image to be tested, the first outline and the second outline respectively corresponding to an outer outline and an inner outline of the optical filter. According to the present solution, the concentricity of an optical filter is measured by using an image processing method, measurement precision for the concentricity of optical filters is improved, and measurement efficiency is also improved.

Description

Filter concentricity measuring method and terminal device

Technical field

The invention belongs to the technical field of industrial detection, and in particular relates to a method for measuring concentricity of a filter and a terminal device.

Background technique

The filter is an optical device used to select the desired radiation band. It can be applied to a camera lens to filter out infrared light and trim incident light. At present, the application requirements of filters are constantly increasing, and the quality requirements for filters are becoming higher and higher. Filter manufacturers continue to standardize the quality requirements of filters while improving the production process. Concentricity is an important quality parameter for filters and needs to be measured during production. The existing concentricity measurement mainly relies on manual measurement. The manual measurement method often has high labor cost, low measurement efficiency, low measurement accuracy, and measurement annotation is not standardized.

technical problem

In view of this, the embodiments of the present invention provide a method for measuring concentricity of a filter and a terminal device, so as to solve the problem that the measurement accuracy of the concentricity of the filter is low and the measurement efficiency is low.

Technical solution

A first aspect of the embodiments of the present invention provides a method for measuring concentricity of a filter, including:

Obtain an initial image containing the filter;

Extracting a target area image from the initial image, using the target area image as an image to be tested; the target area image being an image corresponding to an outer contour of the filter in the initial image;

Denoising the image to be tested;

The center point positions of the first contour and the second contour in the image to be tested subjected to the denoising process are respectively calculated; the first contour and the second contour respectively correspond to an outer contour and an inner contour of the filter.

A second aspect of the embodiments of the present invention provides a filter concentricity measuring apparatus, including:

An acquisition module, configured to acquire an initial image including a filter;

An extraction module, configured to extract a target area image from the initial image, and use the target area image as an image to be tested; the target area image is an image corresponding to an outer contour of the filter in the initial image;

a denoising module, configured to perform denoising processing on the image to be tested;

a calculation module, configured to separately calculate a center point position of the first contour and the second contour in the image to be tested subjected to the denoising process; the first contour and the second contour respectively correspond to an outer contour of the filter And internal contours.

A third aspect of an embodiment of the present invention provides a filter concentricity measuring terminal device including a memory, a processor, and a computer program stored in the memory and operable on the processor, the processor The steps of the method implemented when the computer program is executed include:

Obtain an initial image containing the filter;

Extracting a target area image from the initial image, using the target area as an image to be tested; the target area image being an image corresponding to an outer contour of the filter in the initial image;

Denoising the image to be tested;

A fourth aspect of the embodiments of the present invention provides a computer readable storage medium, where the computer readable storage medium stores a computer program, and the steps of the method implemented when the computer program is executed by the processor include:

Obtain an initial image containing the filter;

Denoising the image to be tested;

Beneficial effect

The embodiment of the present invention processes the initial image including the filter, extracts the image of the target area corresponding to the outer contour of the filter as the image to be tested, and searches for the center point position of the first contour and the second contour in the image to be tested. The first contour and the second contour respectively correspond to the two contours of the filter structure, so the two center point positions found are the center point positions of the two contours in the filter structure, by comparing the two center point positions That is, the measurement of the concentricity of the filter can be achieved. In the embodiment of the invention, the concentricity of the filter is measured by the image processing method, and the measurement precision of the concentricity of the filter can be improved, and the measurement efficiency is improved.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below. It is obvious that the drawings in the following description are only the present invention. For some embodiments, other drawings may be obtained from those of ordinary skill in the art without departing from the drawings.

1 is a flowchart of implementing a method for measuring concentricity of a filter according to an embodiment of the present invention;

2 is an image of a single camera filter provided by an embodiment of the present invention;

3 is an image of a dual camera filter provided by an embodiment of the present invention;

4 is a flowchart of implementing a target area in a method for measuring concentricity of a filter according to an embodiment of the present invention;

FIG. 5 is a flowchart of implementing denoising processing on an image to be measured in a method for measuring concentricity of a filter according to an embodiment of the present invention; FIG.

6 is a flowchart showing an implementation of calculating a center point position of a first contour and a second contour in a method for measuring concentricity of a filter according to an embodiment of the present invention;

7 is a schematic diagram of a filter concentricity measuring device according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of a filter concentricity measuring terminal device according to an embodiment of the present invention.

Embodiments of the invention

In the following description, for purposes of illustration and description However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the invention.

In order to explain the technical solution described in the present invention, the following description will be made by way of specific embodiments.

FIG. 1 is a flowchart of implementing a method for measuring concentricity of a filter according to an embodiment of the present invention, which is described in detail as follows:

In S101, an initial image containing a filter is acquired.

In this embodiment, the filters include, but are not limited to, a single camera filter and a dual camera filter. For image capture of a single camera filter, a single camera filter can be placed on a light-transmissive tool, and a backlight can be used to project from the tool to the back of the single-camera filter. The single camera filter is collected at this time. The filter portion of the image is black and the rest of the background is white. For the image acquisition of the dual camera filter, the coaxial parallel light can be used for illumination. In this case, the image of the dual camera filter is white in the filter and the other background is black. Figure 2 shows an image of several different configurations of single camera filters. Figure 3 shows an image of a dual camera filter.

For concentricity measurement of a single camera filter, the center of the single camera filter is measured and the center of the inner glass is concentric; for the dual camera filter concentricity measurement, the measured is a dual camera The center of the outer structure of the filter glass region and the concentricity of the center of the inner structure of the glass region.

It is to be understood that the number of the filters in the initial image containing the filter may be one, two or more, which is not limited herein. The following embodiments are exemplified by concentricity measurement of a single filter in an image. When two or more filters are included in one image, reference is made to the method of measuring the concentricity of a single filter. Measurements are not repeated.

In S102, a target area image is extracted from the initial image, and the target area image is taken as an image to be tested; the target area image is an image corresponding to an outer contour of the filter in the initial image.

In this embodiment, the obtained initial image containing the filter may include more background parts, and the filter occupies a smaller proportion of the entire image. At this time, if the image processing is directly performed, the processing will be performed. There is too much invalid background information in the image information, which affects the speed of image processing and the accuracy of concentricity measurement. Therefore, the target area image corresponding to the outer contour of the filter may be extracted from the acquired initial image containing the filter, and the target area image is taken as the image to be tested. Subsequent image processing is performed only for the image to be measured, thereby improving the speed of image processing and the measurement accuracy of concentricity.

As an embodiment of the present invention, the target area image can be extracted by locating the position of the filter in the image. As shown in FIG. 4, S102 can include the following steps:

In S401, an outer contour of the filter is determined in the initial image; the outer contour is an outermost contour of the filter.

In this embodiment, the outer contour of the filter can be obtained by performing binarization processing on the acquired initial image. The outer contour refers to the outermost contour of the filter as a whole and the background area, that is, the contour of the area enclosed by the image. Preferably, the initial image is binarized using a large law.

In S402, the filter is positioned according to the external contour to obtain position information of the filter.

In this embodiment, the position of the smallest circumscribed rectangle of the outer contour is the position of the filter. The position information of the filter can be obtained based on the position information of the outer contour.

In S403, the target area image is extracted according to the location information, and the target area image is used as the image to be tested.

In this embodiment, since the image to be measured is subsequently subjected to rotation or the like, the target area is appropriately larger than the position of the filter. The background area of the preset range may be extended to the outside at the position of the filter, and the image to be tested is extracted according to the position of the expanded background area.

Preferably, due to the fact that the filter may not be completely collected on the image in the initial image of the captured filter (for example, the position of the filter is shifted or the position of the image capturing device is shifted) Before extracting the image of the target area, it can be judged according to the outer contour of the filter. If the minimum circumscribed rectangle of the outer contour is all located in the initial image, the initial image is a qualified image, and subsequent image extraction of the target area is performed; if the minimum circumscribed rectangle of the outer contour is not all located in the initial image, the initial image is not The qualified image is deleted, and no subsequent processing is performed.

Preferably, in order to facilitate subsequent processing, the filter in the extracted image to be tested may be rotated and corrected. The step of the rotation correction is: first copying the obtained image to be tested, performing the binarization of the copied image to be tested, and then performing the inversion operation on the image to be tested; extracting each contour in the image to be tested, excluding the maximum Outline outside the contour; extract the minimum circumscribed rectangle for the largest contour, and get the angle and the center of the rectangle. If the angle is less than the preset range, for example, -45 degrees, then the correction angle is the angle plus 90 degrees; The angle and the center of the rectangle are rotated by the affine transformation of the image to be measured. The rotated image is a binarized image, and the image is inverted and returned, and the rotation correction is completed.

In S103, the image to be tested is subjected to denoising processing.

In this embodiment, the image of the filter acquired in S101 may contain defects due to environmental factors or factors of the image acquisition device, etc., for example, black dot noise occurs in a region of a white background, or a black filter region White point noise or the like occurs, so that the subsequently extracted image to be tested also contains noise. Therefore, the image to be measured can be denoised to avoid the measurement accuracy of the concentricity of the filter due to noise.

As an embodiment of the present invention, the image to be tested is compared with the image template subjected to the binarization processing and the inverse processing, and the image to be tested is denoised according to the comparison result. As shown in FIG. 5, S103 may include the following steps:

In S501, a binarization operation and a negation operation are performed on the image to be tested.

In the present embodiment, the binarization operation refers to expressing all pixels of an image by one of two pixel values. For example, the gray value of the pixel on the image is set to 0 or 255, that is, the entire image is presented with a distinct black and white visual effect. The inverse operation is to change the gray value of the pixel from 0 to 255, or from 255 to 0. From the visual effect, the black area and the white area on the image are interchanged.

In S502, each contour in the image to be tested after the binarization operation and the negation operation is extracted; each contour encloses a certain area area.

In the present embodiment, the area enclosed by a certain area refers to the area of the area enclosed by the closed curve constituting the outline. After the image to be tested is binarized and inverted, the image may contain white point noise or black point noise. Wherein, the area enclosed by the contour corresponding to the noise tends to be small, and the area enclosed by the contour corresponding to the filter is usually large, so the noise and the filtering can be distinguished by comparing the area enclosed by the contour. sheet. The area enclosed by each contour is sorted from large to small. The area of the area with a larger area is the contour corresponding to the filter, and the area of the area with a smaller area is the contour corresponding to the noise.

In S503, the front preset number of contours in the area of each contour in each contour is used as a template.

In the present embodiment, the front predetermined number of contours of the area from large to small refers to a preset number of contours in which the area enclosed by the contour is large. For example, if the preset number is 2, the contour with the largest area of the area enclosed in each contour and the contour with the largest area of the surrounding area are included, and the images of the two contours are included as templates.

As an embodiment of the present invention, each contour can be sorted according to the area of the enclosed area, and the area enclosed by the smaller number of the outline is larger. A profile that is less than or equal to the preset contour number is used as a template. For example, if the contour numbers are 1, 2, 3, ..., n in order, the area enclosed by the contour No. 1 is the largest. If the preset contour number is 2, the contours of the sequence numbers 3, 4, ..., n are removed, and only the contours with the sequence number 1 and the sequence number 2 are reserved as templates. Therefore, in this way, the contour corresponding to the noise is removed, only the contour corresponding to the filter is retained, and the contour containing the preset number is generated to generate a template for denoising comparison.

In S504, comparing the image to be tested and the template, the image to be tested is processed according to the comparison result.

In this embodiment, the template obtained by S503 is an image containing only the corresponding contour of the filter, and the image is subjected to the inversion operation, so the template is interchanged with the black area and the white area of the image to be tested. By comparing the image to be tested and the template, the contours of the image to be tested that do not exist in the template are removed, and the denoising process of the image to be measured can be realized. Removing the contours can set the point pixel values of the regions within the contour to coincide with the values of the pixels near the outside of the contour. Specifically, comparing the pixel values of the corresponding pixels in the image to be tested and the template respectively, if the pixel values of the pixels in the two images are inconsistent, the pixel values of the pixel in the image to be tested remain unchanged; if two images are in the image If the pixel values of the pixels are the same, the pixel value of the pixel in the image to be tested is inverted (for example, the white point is changed to a black point).

By performing denoising processing on the image to be measured, noise pixel points in the image to be tested can be reduced, thereby improving the measurement accuracy of the concentricity of the filter.

In S104, central point positions of the first contour and the second contour in the image to be tested subjected to the denoising process are respectively calculated; the first contour and the second contour respectively correspond to an outer contour of the filter and Internal outline.

In this embodiment, the structure of the filter includes an outer contour and an inner contour. The first contour in the image to be tested corresponds to the outer contour of the filter, and the second contour in the image to be tested corresponds to the inner contour of the filter. Since the image to be measured may contain contours such as noise, only the center point positions of the first contour and the second contour are calculated when performing the concentricity measurement. The concentricity can be expressed by the distance between the center point of the outer contour of the filter and the center point of the inner contour, so that the filter can be realized by calculating the center point position of the first contour and the center point position of the second contour. Measurement of concentricity.

As an embodiment of the present invention, the four edge positions of the rectangle corresponding to the first contour and the second contour may be searched, and the center point position of the rectangle is determined by the four positions of the rectangle. As shown in FIG. 6, S104 may include the following steps:

In S601, four edge positions of the rectangle corresponding to the first contour and the second contour in the image to be tested are respectively searched.

In S602, four vertex positions of the rectangle corresponding to the first contour and the second contour are respectively calculated according to the four edge positions.

In S603, the center point positions of the rectangles corresponding to the first contour and the second contour are respectively calculated according to the four vertex positions.

In this embodiment, the structures of the single camera filter and the dual camera filter respectively correspond to two rectangles inside and outside, so in the image to be tested, the first contour and the second contour respectively correspond to a rectangle, and the rectangle can be searched by The position of the four edges is to determine the position of the rectangle. Then, the four vertex positions of the rectangle are calculated by four edges, and the two vertices of the diagonal of the rectangle are connected into a diagonal line. The intersection position of the two diagonal lines of the rectangle is the center point position of the rectangle, so it can be separately obtained. The center point position of the first contour and the second contour.

The rectangle corresponding to the first contour may be a minimum circumscribed rectangle of the first contour, or may be a maximum inscribed rectangle of the first contour; the rectangle corresponding to the second contour may be a minimum circumscribed rectangle of the second contour, or may be The maximum inscribed rectangle of the second contour; the specific setting can be selected according to the actual situation, which is not limited herein.

The position of the center point of the first contour may be calculated first, and then the center point position of the second contour may be calculated, or the center point position of the second contour may be calculated first, and then the center point position of the first contour may be calculated, or two center points may be separately calculated at the same time. Location, not limited here.

The following is an example of a single camera filter and a dual camera filter.

For the single camera filter, first extracting the second contour, determining whether the height and width of the rectangle corresponding to the second contour conform to the size parameter of the filter, and if the height and width of the rectangle corresponding to the second contour do not meet the preset The size parameter range of the filter is not subjected to subsequent processing of the image to be measured, and an error message is returned; if the height and width of the rectangle corresponding to the second contour conform to the size parameter range of the preset filter, respectively Extract the area within the preset range near the four edges of the rectangle (for example, the area extracted from the upper line may be the area where the upper line is the center and the height is half the height of the rectangle; the area extracted from the left line may be the center of the left line, the height An area that is half the width of the rectangle). Find the edge points adjacent to the black and white pixels in the extracted area, and straighten the edge points to obtain the four edges of the rectangle corresponding to the second contour, and further determine the center of the rectangle corresponding to the second contour. Point location.

Preferably, the least squares straight line fitting is used, and the fitting is performed twice in succession, and after the first straight line fitting, the point where the straight line distance of the first fitting is greater than the preset distance is deleted, and the remaining Click the second straight line to fit. The line thus fitted is more accurate, thereby improving the accuracy of concentricity detection.

Finding four edges of the rectangle corresponding to the first contour outward according to the center point position of the rectangle corresponding to the second contour, respectively extracting regions within a preset range near the four edges of the rectangle. Find the edge points adjacent to the black and white pixels in the extracted area, and straighten the edge points to obtain the four edges of the rectangle corresponding to the first contour, and further find the center of the rectangle corresponding to the first contour. Point location.

If the difference between the center point position of the first contour and the center point position of the second contour is less than or equal to a preset value, the filter concentricity measurement result is qualified; if the center point position of the first contour is If the difference between the center point positions of the two contours is greater than a preset value, the filter concentricity measurement result is acceptable; in addition, the value of the filter concentricity may be returned.

For the dual camera filter, the first contour is first extracted, and the minimum circumscribed rectangle of the first contour is obtained according to the first contour to obtain the center point position of the minimum circumscribed rectangle. Extending outward according to the center point position of the minimum circumscribed rectangle, searching for four edges of the rectangle corresponding to the second contour, respectively extracting regions within a preset range near the four edges of the rectangle. Find the edge points adjacent to the black and white pixels in the extracted area, and straighten the edge points to obtain the four edges of the rectangle corresponding to the second contour, and further determine the center of the rectangle corresponding to the second contour. Point location.

As shown in Fig. 3, the outer frame area of the dual camera filter is a rectangular area with the annular area formed by the middle rectangle removed. According to the position of the center point of the rectangle corresponding to the second contour, the outer region is extended to find the annular region, and the edge points adjacent to the black and white pixel points are searched in the annular region, and the edge points are straight-line fitted to obtain the first The four edges of the rectangle corresponding to the contour further determine the position of the center point of the rectangle corresponding to the first contour.

As an embodiment of the present invention, since there are various shapes of the filter parts, for some structures, the rectangular shape of the filter in the image to be tested needs to be compensated, and S401 may include: according to the shape information of the filter, The position of the edge of the four edges of the rectangle corresponding to the first contour or the second contour to be compensated is compensated.

In the present embodiment, as shown in FIG. 2, the structure type of the single camera filter includes a square structure, a concave structure, a convex structure, a concave structure on the upper and lower sides, and the like. The shape information of the single camera filter includes, but is not limited to, convex width, convex height, upper concave width, upper concave height, lower concave width, lower concave height, overall part width and height, pixel precision, and judgment standard value. One or more. The shape information of the dual camera filter includes, but is not limited to, one or more of the width, height, and pixel dimensions of the part.

For a single camera filter, if the structure of the filter is a convex structure or a square structure, it is not necessary to compensate for the four edges of the rectangle corresponding to the first contour. If the structure of the filter is a concave structure or a concave structure, the four edges of the rectangle corresponding to the first contour need to be compensated. Because of the filter of the concave structure or the concave structure of the upper and lower sides, the edge of the edge of the black and white pixel found from the image to be tested is not the edge of the rectangle corresponding to the outer contour of the filter, that is, not corresponding to the first contour. The edge of the rectangle can only be obtained by compensating the corresponding rectangular edge of the first contour, and then the center point position of the first contour.

Specifically, the edge of the black-and-white pixel edge point found from the image to be tested may be compensated in the corresponding direction according to the information of the upper concave width, the upper concave height, the lower concave width, and the lower concave height in the shape information of the filter. , thereby obtaining the four edges of the rectangle corresponding to the first contour. For example, if the direction of the depression of the concave structure or the concave and convex structural filter is defined as the Y direction, the edge of the found black and white pixel edge point is compensated in the Y direction.

As an embodiment of the present invention, in order to facilitate finding the contour edge of the filter in the image to be tested, a plurality of regions may be provided for the filters of different structure types. For convenience of explanation, the upper, lower, left, and right directions in the directions indicated in the following description are referred to by the part image in FIG. 2. Single camera filters have four configurations. Taking the embossed structure as an example, the area of the uppermost convex portion is set as the first area, the right side area of the part is set as the second area, and the lower area of the part is set as the third area, and the left side area of the part is set. Set to the fourth area. The locale of the other three structures refers to the locale of the convex structure.

When you find the edge of a black and white pixel edge point in the outline, you can scan the four areas separately. Among them, one or three areas use column scanning, and the second and fourth areas use line scanning. When the pixel value of the scanned pixel changes, the current row or column scan is stopped, and the next row or column scan is continued, and the coordinates of the point are saved. When the scanning of the four areas is completed, the saved point coordinates are processed. The point coordinates obtained by one or three regions are arranged in descending order according to the Y coordinate, and some points before and after the Y coordinate are excluded; the point coordinates obtained by the second and fourth regions are arranged in accordance with the X coordinate from large to small, and Exclude a portion of the X coordinate front and back. According to the coordinates of the found points, a straight line fit can be performed to find the four edges of the rectangle corresponding to the outer contour or the inner contour of the filter.

By setting the area, the edge of the rectangle corresponding to the contour in the image to be measured is searched more efficiently, and the processing speed of the image is improved, thereby improving the measurement speed of the concentricity of the filter.

In summary, the embodiments of the present invention have the following advantages, specifically: 1. The production process is simple; 2. The measurement accuracy is high, the measurement accuracy is 0.005MM; 3. The measurement filter has many kinds of shapes, and can be adapted to a plurality of different sizes. The filter; 4. The method is simple, easy to maintain, can adapt to the actual engineering environment, and has high reliability. Therefore, the embodiments of the present invention can effectively overcome the difficulty that the prior art is difficult to solve in practical applications, and can truly achieve high-accuracy and high-efficiency measurement of the concentricity of the filter.

In addition, the embodiments of the present invention are directed to the need for quality inspection of filter production, and the use of computer vision technology to apply advanced image processing algorithms to engineering practice, enabling high-precision measurement of filter concentricity with maintenance The advantages of simple operation and high reliability, especially for different types of filters produced on the production line, can meet the measurement requirements. A set of measuring equipment to meet the needs of a full set of product quality testing.

It should be understood that the size of the sequence of the steps in the above embodiments does not imply a sequence of executions, and the order of execution of the processes should be determined by its function and internal logic, and should not be construed as limiting the implementation of the embodiments of the present invention.

Corresponding to the filter concentricity measuring method described in the above embodiments, FIG. 7 is a schematic diagram of the filter concentricity measuring device provided by the embodiment of the present invention. For the convenience of explanation, only the parts related to the present embodiment are shown.

Referring to FIG. 7, the apparatus includes an acquisition module 71, an extraction module 72, a denoising module 73, and a calculation module 74.

The obtaining module 71 is configured to acquire an initial image including a filter.

The extracting module 72 is configured to extract a target area image from the initial image, and use the target area image as an image to be tested; the target area image is an image in the initial image corresponding to an outer contour of the filter.

The denoising module 73 is configured to perform denoising processing on the image to be tested.

a calculation module 74, configured to separately calculate a center point position of the first contour and the second contour in the image to be tested subjected to the denoising process; the first contour and the second contour respectively correspond to an outer portion of the filter Outline and internal contours.

Preferably, the extraction module 72 is configured to:

Determining an outer contour of the filter in the initial image; the outer contour being an outermost contour of the filter;

Positioning the filter according to the outer contour to obtain position information of the filter;

Extracting the target area image according to the location information, and using the target area image as the image to be tested.

Preferably, the denoising module 73 is configured to:

Performing a binarization operation and a negation operation on the image to be tested;

Extracting each contour in the image to be tested after the binarization operation and the inversion operation; each contour respectively encloses a certain area area;

Pre-predetermined number of contours of the area in each contour from large to small as a template;

Comparing the image to be tested and the template, the image to be tested is processed according to the comparison result.

Preferably, the calculation module 74 is configured to:

Searching, respectively, four edge positions of the rectangle corresponding to the first contour and the second contour in the image to be tested;

Calculating four vertex positions of the rectangle corresponding to the first contour and the second contour according to the four edge positions;

Calculating a center point position of the rectangle corresponding to the first contour and the second contour according to the four vertex positions.

Preferably, the calculation module 74 is configured to:

The position of the edge of the four edges of the rectangle corresponding to the first contour or the second contour to be compensated is compensated according to the shape information of the filter.

FIG. 8 is a schematic diagram of a filter concentricity measuring terminal device according to an embodiment of the present invention. As shown in FIG. 8, the filter concentricity measuring terminal device 8 of this embodiment includes a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and operable on the processor 80, For example, the filter concentricity measurement program. When the processor 80 executes the computer program 82, the steps in the above embodiments of the respective filter concentricity measuring methods are implemented, such as steps 101 to 104 shown in FIG. Alternatively, the processor 80, when executing the computer program 82, implements the functions of the modules/units in the various apparatus embodiments described above, such as the functions of the modules 71-74 shown in FIG.

Illustratively, the computer program 82 can be partitioned into one or more modules/units that are stored in the memory 81 and executed by the processor 80 to complete this invention. The one or more modules/units may be a series of computer program instruction segments capable of performing a particular function, the instruction segments being used to describe the execution of the computer program 82 in the filter concentricity measurement terminal device 8. . For example, the computer program 82 can be divided into an acquisition module, an extraction module, a denoising module, and a calculation module, and the specific functions of each module are as follows:

The filter concentricity measuring terminal device 8 may be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server. The filter concentricity measuring terminal device may include, but is not limited to, a processor 80 and a memory 81. It will be understood by those skilled in the art that FIG. 8 is only an example of the filter concentricity measuring terminal device 8, and does not constitute a limitation of the filter concentricity measuring terminal device 8, and may include more or less than the illustration. Components, or combinations of certain components, or different components, such as the filter concentricity measurement terminal device may also include input and output devices, network access devices, buses, and the like.

The so-called processor 80 can be a central processing unit (Central Processing Unit, CPU), can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like.

The memory 81 may be an internal storage unit of the filter concentricity measuring terminal device 8, such as a hard disk or a memory of the filter concentricity measuring terminal device 8. The memory 81 may also be an external storage device of the filter concentricity measuring terminal device 8, for example, a plug-in hard disk equipped with the filter concentricity measuring terminal device 8, and a smart memory card (Smart Media Card) , SMC), Secure Digital (SD) card, flash card (Flash Card) and so on. Further, the memory 81 may also include both the internal storage unit of the filter concentricity measuring terminal device 8 and an external storage device. The memory 81 is used to store the computer program and other programs and data required for the filter concentricity measurement terminal device. The memory 81 can also be used to temporarily store data that has been output or is about to be output.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, only the division of each functional unit and module described above is exemplified. In practical applications, the above functions may be assigned to different functional units according to needs. The module is completed by dividing the internal structure of the device into different functional units or modules to perform all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit, and the integrated unit may be implemented by hardware. Formal implementation can also be implemented in the form of software functional units. In addition, the specific names of the respective functional units and modules are only for the purpose of facilitating mutual differentiation, and are not intended to limit the scope of protection of the present application. For the specific working process of the unit and the module in the foregoing system, reference may be made to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the above embodiments, the descriptions of the various embodiments are different, and the parts that are not detailed or described in the specific embodiments may be referred to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods for implementing the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present invention.

In the embodiments provided by the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the device/terminal device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units. Or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, the present invention implements all or part of the processes in the foregoing embodiments, and may also be completed by a computer program to instruct related hardware. The computer program may be stored in a computer readable storage medium. The steps of the various method embodiments described above may be implemented when the program is executed by the processor. Wherein, the computer program comprises computer program code, which may be in the form of source code, object code form, executable file or some intermediate form. The computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard drive, a magnetic disk, an optical disk, a computer memory, a read only memory (ROM, Read-Only) Memory), random access memory (RAM, Random) Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. It should be noted that the content contained in the computer readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in a jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, computer readable media It does not include electrical carrier signals and telecommunication signals.

The embodiments described above are only for explaining the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that The technical solutions described in the examples are modified, or some of the technical features are equivalently replaced; and the modifications or substitutions do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in Within the scope of protection of the present invention.

Claims

A method for measuring concentricity of a filter, comprising:

Obtain an initial image containing the filter;

Extracting a target area image from the initial image, using the target area image as an image to be tested; the target area image being an image corresponding to an outer contour of the filter in the initial image;

Denoising the image to be tested;

The center point positions of the first contour and the second contour in the image to be tested subjected to the denoising process are respectively calculated; the first contour and the second contour respectively correspond to an outer contour and an inner contour of the filter.
The filter concentricity measuring method according to claim 1, wherein the presenting the target area image from the initial image, and using the target area image as the image to be tested comprises:

Determining an outer contour of the filter in the initial image; the outer contour being an outermost contour of the filter;

Positioning the filter according to the outer contour to obtain position information of the filter;

Extracting the target area image according to the location information, and using the target area image as the image to be tested.
The filter concentricity measuring method according to claim 1, wherein the performing denoising processing on the image to be tested comprises:

Performing a binarization operation and a negation operation on the image to be tested;

Extracting each contour in the image to be tested after the binarization operation and the inversion operation; each contour respectively encloses a certain area area;

Pre-predetermined number of contours of the area in each contour from large to small as a template;

Comparing the image to be tested and the template, the image to be tested is processed according to the comparison result.
The filter concentricity measuring method according to any one of claims 1 to 3, wherein the calculating a center point position of the first contour and the second contour in the image to be tested subjected to the denoising processing, respectively include:

Searching, respectively, four edge positions of the rectangle corresponding to the first contour and the second contour in the image to be tested;

Calculating four vertex positions of the rectangle corresponding to the first contour and the second contour according to the four edge positions;

Calculating a center point position of the rectangle corresponding to the first contour and the second contour according to the four vertex positions.
The filter concentricity measuring method according to claim 4, wherein the searching for the four edge positions of the rectangle corresponding to the first contour and the second contour in the image to be tested respectively comprises:

The position of the edge of the four edges of the rectangle corresponding to the first contour or the second contour to be compensated is compensated according to the shape information of the filter.
A filter concentricity measuring device, comprising:

An acquisition module, configured to acquire an initial image including a filter;

An extraction module, configured to extract a target area image from the initial image, and use the target area image as an image to be tested; the target area image is an image corresponding to an outer contour of the filter in the initial image;

a denoising module, configured to perform denoising processing on the image to be tested;

a calculation module, configured to separately calculate a center point position of the first contour and the second contour in the image to be tested subjected to the denoising process; the first contour and the second contour respectively correspond to an outer contour of the filter And internal contours.
The filter concentricity measuring apparatus according to claim 6, wherein the extraction module is configured to:

Determining an outer contour of the filter in the initial image; the outer contour being an outermost contour of the filter;

Positioning the filter according to the outer contour to obtain position information of the filter;

Extracting the target area image according to the location information, and using the target area image as the image to be tested.
The filter concentricity measuring device according to claim 6, wherein the denoising module is configured to:

Performing a binarization operation and a negation operation on the image to be tested;

Extracting each contour in the image to be tested after the binarization operation and the inversion operation; each contour respectively encloses a certain area area;

Pre-predetermined number of contours of the area in each contour from large to small as a template;

Comparing the image to be tested and the template, the image to be tested is processed according to the comparison result.
A filter concentricity measuring terminal device comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein when the processor executes the computer program The steps of the method of any one of claims 1 to 5.
A computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 5.