CN112101200A - Human face anti-recognition method, system, computer equipment and readable storage medium - Google Patents
Human face anti-recognition method, system, computer equipment and readable storage medium Download PDFInfo
- Publication number
- CN112101200A CN112101200A CN202010964608.1A CN202010964608A CN112101200A CN 112101200 A CN112101200 A CN 112101200A CN 202010964608 A CN202010964608 A CN 202010964608A CN 112101200 A CN112101200 A CN 112101200A
- Authority
- CN
- China
- Prior art keywords
- face
- information
- characteristic
- face image
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000001514 detection method Methods 0.000 claims abstract description 28
- 238000004590 computer program Methods 0.000 claims description 21
- 230000001815 facial effect Effects 0.000 claims description 15
- 238000000605 extraction Methods 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 230000009466 transformation Effects 0.000 claims description 5
- 238000003062 neural network model Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 230000010354 integration Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 14
- 238000010586 diagram Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Collating Specific Patterns (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The embodiment of the invention relates to the technical field of face recognition, and particularly discloses a face anti-recognition method, a face anti-recognition system, computer equipment and a readable storage medium, wherein the face anti-recognition method provided by the embodiment of the invention obtains a face image to be recognized in front of a display screen; extracting regional characteristic information in the face image; matching the regional characteristic information with a preset human face characteristic database; confirming the identity information of a face image to be recognized; acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information; therefore, in the process of face recognition of people, the face image information recognized at present is not easy to be maliciously recognized by others, and the safety of the face image information recognized at present is guaranteed.
Description
Technical Field
The embodiment of the invention relates to the technical field of face recognition, in particular to a face anti-recognition method, a face anti-recognition system, computer equipment and a readable storage medium.
Background
The face recognition technology is a biological recognition mode which is developed earlier, and the current face recognition technology is more and more widely applied, for example: face recognition access control system, monitoring system, etc. It has become a focus of great concern in the field of artificial intelligence and pattern recognition research. Therefore, various face recognition algorithms, such as feature extraction, dimension control, recognition accuracy and the like, appear. Because the dimension of the face image is relatively high, the common method is to perform dimension reduction on the face image to extract a characteristic face, and then perform comparison.
The method has achieved good identification effect, but with the development of the information era, the requirement for the security of personal data is higher and higher, people begin to pay attention to the security of personal information, and the traditional face identification technology, during the process of face identification, the face image information of people is easy to be maliciously utilized by other people, which can threaten the information security of people; therefore, a human face anti-recognition method is needed to ensure the safety of the currently recognized human face image information.
Disclosure of Invention
The embodiment of the invention aims to provide a face anti-recognition method, a face anti-recognition system, computer equipment and a readable storage medium, so that the face image information recognized currently is not easy to be maliciously recognized by others in the face recognition process of people, and the safety of the face image information recognized currently is guaranteed.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a human face anti-recognition method is applied to a computer device with a display screen, and the method comprises the following steps:
acquiring a face image to be recognized in front of the display screen;
extracting regional characteristic information in the face image;
matching the regional characteristic information with a preset human face characteristic database;
acquiring standard face information matched with the regional characteristic information of the face image in a face characteristic database, and confirming the identity information of the face image to be recognized when the matching degree of the standard face information and the regional characteristic information of the face image is greater than a preset matching degree;
the method comprises the steps of obtaining regional characteristic information of a confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information.
As a further limitation of the technical solution of the embodiment of the present invention, the method for forming the face feature database includes the following specific steps:
acquiring the feature information of the face region in the face picture library;
integrating the human face characteristic points of the human face region characteristic information to form a corresponding characteristic human face image in the human face picture library;
and acquiring the characteristic face images in all the face picture libraries in a face database to form the face characteristic database.
As a further limitation of the technical solution of the embodiment of the present invention, the step of acquiring the standard face information includes:
acquiring a characteristic face image in a face characteristic database;
detecting the characteristic face image through a cascade multitask convolution neural network model to obtain face characteristic points of the characteristic face image;
carrying out approximate transformation on the characteristic face image based on the facial feature points of the characteristic face image and the facial feature points of a standard image to obtain the standard face image with the standard face information; and preprocessing the standard face image by random brightness, contrast and saturation to obtain the standard face information.
As a further limitation of the technical solution of the embodiment of the present invention, the region feature information in the face image includes feature point information formed by the left eye, the right eye, the nose, the mouth, and the chin of the face, and the recognition of the face image is realized by acquiring the feature point information.
As a further limitation of the technical solution of the embodiment of the present invention, the method further includes: before the face image to be recognized in front of the display screen is obtained, detecting that a camera of the display screen on the computer equipment is in an open state, and adjusting the brightness of the display screen to a maximum value.
A human face anti-recognition system is applied to a computer device with a display screen, and comprises:
the first acquisition module is used for acquiring a face image to be recognized in front of the display screen;
the extraction module is used for extracting regional characteristic information in the face image;
the matching module is used for matching the region characteristic information with a preset human face characteristic database;
the second acquisition module is used for acquiring standard face information matched with the regional characteristic information of the face image in the face characteristic database, and confirming the identity information of the face image to be recognized when the matching degree of the standard face information and the regional characteristic information of the face image is greater than the preset matching degree;
the detection and identification module is used for acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information.
As a further limitation of the technical solution of the embodiment of the present invention, the face anti-recognition system further includes: and the detection adjusting module is used for detecting that a camera of a display screen on the computer equipment is in an opening state and adjusting the brightness of the display screen to a maximum value.
As a further limitation of the technical solution of the embodiment of the present invention, the face anti-recognition system further includes a device for forming the face feature database, and specifically includes:
the third acquisition module is used for acquiring the feature information of the face area in the face picture library;
the integration module is used for integrating the human face characteristic points of the human face region characteristic information to form a corresponding characteristic human face image in the human face picture library;
and the fourth acquisition module is used for acquiring the characteristic face images in all the face picture libraries in the face database to form the face characteristic database.
A computer device comprising a display screen, a memory, a processor and a computer program, wherein the memory has stored therein the computer program which, when executed by the processor, causes the processor to carry out the steps of the anti-face recognition method.
A readable storage medium having stored thereon a computer program which, when executed by a processor, causes the processor to perform the steps of the anti-face recognition method.
Compared with the prior art, the invention has the beneficial effects that:
the human face anti-recognition method provided by the embodiment of the invention obtains the human face image to be recognized in front of the display screen; extracting regional characteristic information in the face image; matching the regional characteristic information with a preset human face characteristic database; confirming the identity information of a face image to be recognized; acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information; therefore, in the process of face recognition of people, the face image information recognized at present is not easy to be maliciously recognized by others, and the safety of the face image information recognized at present is guaranteed.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a flowchart of a face anti-recognition method provided in embodiment 1 of the present invention.
Fig. 2 is a schematic structural diagram of a human face anti-recognition system provided in embodiment 1 of the present invention.
Fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Fig. 4 is a flowchart of a face anti-recognition method according to embodiment 2 of the present invention.
Fig. 5 is a schematic structural diagram of a human face anti-recognition system provided in embodiment 2 of the present invention.
FIG. 6 is a diagram illustrating a connection relationship between a readable storage medium and a processor according to an embodiment of the present invention.
Fig. 7 is a flowchart of a method for forming a face feature database according to an embodiment of the present invention.
Fig. 8 is a flowchart of a step of acquiring standard face information in the embodiment of the present invention.
Fig. 9 is a block diagram of an apparatus for forming the facial feature database according to an embodiment of the present invention.
Fig. 10 is a block diagram of an apparatus for acquiring the standard face information according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that, although the terms first, second, etc. may be used herein to describe various functional blocks in embodiments of the present invention, these functional blocks should not be limited by these terms. These terms are only used to distinguish one type of functional module from another. For example, a first determination module may also be referred to as a second determination module without necessarily requiring or implying any such actual relationship or order between such entities or operations without departing from the scope of embodiments of the present invention. Similarly, the second determination module may also be referred to as the first determination module. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
It can be understood that, in the conventional face recognition technology, when a face image (such as a photo) of a user is illegally acquired by a malicious person, a potential safety hazard is likely to be brought to information of the user.
In the embodiment of the invention, a face image to be recognized in front of the display screen is obtained; extracting regional characteristic information in the face image; matching the regional characteristic information with a preset human face characteristic database; confirming the identity information of a face image to be recognized; acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information; therefore, the face image information can be protected in the process of face recognition of people, and the information safety of people is guaranteed.
Example 1
Fig. 1 shows an implementation process of a face anti-recognition method provided in embodiment 1 of the present invention, where the face anti-recognition method is applied to a computer device with a display screen, and the computer device may be a mobile phone, a notebook, or other device capable of performing communication, and is not particularly limited to the following, and the face anti-recognition method is detailed as follows:
and S100, acquiring a face image to be recognized in front of the display screen.
In the embodiment of the present invention, when face recognition is required, a camera on a computer device is used to photograph a face image of a user, and then feature point information formed by a left eye, a right eye, a nose, a mouth, and a chin of the user in the photograph is extracted.
And step S200, extracting regional characteristic information in the face image.
In the embodiment of the present invention, the information in the face image acquired in step S100 is extracted, and the extraction content is selected according to needs, which may be but only the region feature information of the face image near the nose, or only include the region feature information of the face image near the nose and near the chin, or certainly may be at least one of the left eye, the right eye, the nose, the mouth, and the chin randomly selected as the region feature information of the face image, and certainly, in order to improve the success rate of face recognition, at least three of the left eye, the right eye, the nose, the mouth, and the chin are selected as the region feature information, which can significantly improve the success rate of face recognition, it can be understood that the example of extracting and selecting the face image region feature information here is only a convenient understanding scheme, and the extracting and selecting of the region feature information of a specific face image can be flexibly performed according to actual needs, and are not limited herein.
And step S300, matching the regional characteristic information with a preset human face characteristic database.
In addition, fig. 7 shows a flow chart of a method for forming the face feature database according to an embodiment of the present invention, where the method for forming the face feature database according to the embodiment of the present invention includes the following specific steps:
acquiring the feature information of the face region in the face picture library;
integrating the human face characteristic points of the human face region characteristic information to form a corresponding characteristic human face image in the human face picture library;
and acquiring the characteristic face images in all the face picture libraries in a face database to form the face characteristic database.
In the embodiment provided by the present invention, the regional characteristic information extracted in step S200 is matched with the original preset face characteristic database, it can be understood that a set of face image characteristic information of all authorized users forms a face picture library, and the acquisition mode of the face picture library is to perform face recognition on each authorized user and store the regional characteristic information of the face image thereof to obtain a data basis of the set of face image characteristic information in the face characteristic database, that is, to form the face picture library.
In addition, it can be understood that, in the embodiment of the present invention, the region feature information in the face image includes feature point information formed by the left eye, the right eye, the nose, the mouth, and the chin of the face, and the recognition of the face image is realized by acquiring the feature point information.
Step S400, obtaining standard face information matched with the region feature information of the face image in a face feature database, and confirming the identity information of the face image to be recognized when the matching degree of the standard face information and the region feature information of the face image is greater than a preset matching degree.
In the embodiment of the invention, after the computer equipment identifies the face image information, extracting the regional characteristic information of the face image information, acquiring the standard face information from the face characteristic database, after acquiring the standard face information, comparing the matching degree of the regional characteristic information of any face image, confirming the identity information of the face image to be identified when the matching degree of the standard face information and the regional characteristic information of the face image is greater than the preset matching degree, and otherwise, when the matching degree of the standard face information and the regional characteristic information of the face image is less than the preset matching degree, indicating that the user performing face identification is an unauthorized user, further failing to confirm the identity information of the face image to be identified, and confirming that the user is an unauthorized user.
In addition, fig. 8 shows a flow chart of acquiring the standard face information in a preferred embodiment of the present invention, and specifically, in the preferred embodiment of the present invention, a step of acquiring the standard face information is provided, where the step includes:
acquiring a characteristic face image in a face characteristic database;
detecting the characteristic face image through a cascade multitask convolution neural network model to obtain face characteristic points of the characteristic face image;
carrying out approximate transformation on the characteristic face image based on the facial feature points of the characteristic face image and the facial feature points of a standard image to obtain the standard face image with the standard face information; and preprocessing the standard face image by random brightness, contrast and saturation to obtain the standard face information.
Step S500, obtaining the regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information.
In the embodiment of the invention, the regional characteristic information of the face image information of the authorized user after the face identification confirmation is replaced, the replacement can be randomly replacing at least one of the left eye, the right eye, the nose, the mouth and the chin, a unique identifier is generated in the replacement process, in the specific implementation, the unique identifier is generated through a hash algorithm at the position point of the regional characteristic of the face image, and the identifier is written into the last position for storage, so that the safety of the modified image data is improved.
According to the scheme provided by the embodiment, the identifier is generated by the preset algorithm for the regional characteristic information of the current face image information, and the identifier is written into the current recognized face image information, so that the processed current recognized face image information is not easy to be maliciously recognized by others, and the safety of the current recognized face image information is guaranteed.
Fig. 4 shows another preferred embodiment provided by the embodiment of the present invention, in which the face anti-recognition method further includes the following steps:
step S600, before obtaining the face image to be recognized in front of the display screen, detecting that the camera 23 of the display screen 21 on the computer device 20 is in an open state, and adjusting the brightness of the display screen 21 to a maximum value.
It can be understood that the face image information may be preprocessed before the face image information of the user is acquired, for example, the preprocessing may be at least one of light compensation of the face image, face image denoising, and face image filtering, so as to ensure validity of the acquired face image information data of the user, and improve processing efficiency of the face image information data.
Fig. 2 shows a block diagram of a face anti-recognition system according to a further embodiment of the present invention, where the face anti-recognition system is applied to a computer device having a display screen, and the face anti-recognition system 10 includes:
the first acquisition module 11 is configured to acquire a face image to be recognized in front of the display screen;
an extraction module 12, configured to extract regional feature information in the face image;
in the embodiment of the present invention, when face recognition is required, the first obtaining module 11 is used to take a picture of a face image of a user, and then the extracting module 12 is used to obtain feature point information formed by the left eye, the right eye, the nose, the mouth, and the chin of the user in the picture.
The matching module 13 is used for matching the region feature information with a preset human face feature database;
the second obtaining module 14 is configured to obtain standard face information in a face feature database, where the standard face information matches with the regional feature information of the face image, and when the matching degree between the standard face information and the regional feature information of the face image is greater than a preset matching degree, determine identity information of the face image to be recognized;
the detection and recognition module 15 is configured to acquire regional feature information of the confirmed face image, replace the regional feature information to generate target face information, recognize the target face information by using detection equipment, and store the target face information when the detection equipment cannot recognize the target face information.
Fig. 5 shows another preferred embodiment of the present invention, in which the anti-face recognition system 10 further includes: and the detection adjusting module 16 is configured to detect that the camera 23 of the display screen 21 on the computer device 20 is in an on state, and adjust the brightness of the display screen 21 to a maximum value.
The human face anti-recognition system provided by the embodiment of the invention further comprises a device 50 for forming the human face feature database;
fig. 9 is a block diagram illustrating an apparatus 50 for forming the facial feature database according to an embodiment of the present invention, where the apparatus 50 for forming the facial feature database includes:
a third obtaining module 51, configured to obtain face region feature information in the face picture library;
an integrating module 52, configured to integrate the face feature points of the face region feature information to form a feature face image corresponding to the face image library;
a fourth obtaining module 53, configured to obtain the feature face images in all the face image libraries in the face database, so as to form the face feature database.
In the embodiment provided by the present invention, the regional characteristic information extracted by the extraction module 12 is used to match with the original preset face characteristic database, it can be understood that the set of face image characteristic information of all authorized users forms the face picture library, and the acquisition mode of the face picture library is to perform face recognition on each authorized user and store the regional characteristic information of the face image thereof, so as to obtain the data basis of the set of face image characteristic information in the face characteristic database, that is, form the face picture library.
Further, in the embodiment provided by the present invention, the human face anti-recognition system further provided by the embodiment of the present invention further includes a device 60 for acquiring the standard human face information;
fig. 10 shows a block diagram of an apparatus 60 for acquiring the standard face information according to an embodiment of the present invention, where the apparatus 60 for acquiring the standard face information specifically includes:
a fifth obtaining module 61, configured to obtain a characteristic face image in a face characteristic database;
a detection module 62, configured to detect the feature face image through a cascaded multi-task convolutional neural network model to obtain facial feature points of the feature face image;
an image processing module 63, configured to perform approximate transformation on the feature face image based on the facial feature points of the feature face image and the facial feature points of a standard image to obtain a standard face image with the standard face information; and preprocessing the standard face image by random brightness, contrast and saturation to obtain the standard face information.
Fig. 3 shows a schematic structural diagram of a computer device provided in an embodiment of the present invention, the computer device includes a display screen 21, a memory 22, a processor 24, and a computer program 25, where the memory 22 stores the computer program 25, and when the computer program 25 is executed by the processor 24, the processor 24 executes the steps of the face anti-recognition method.
It is understood that, in the preferred embodiment provided by the present invention, the computer device may also be a notebook computer, a Personal Digital Assistant (PDA), a mobile phone, or other devices capable of communicating.
Fig. 6 shows a schematic diagram of a readable storage medium 30, the readable storage medium 30 stores a computer program 25, and when the computer program 25 is executed by the processor 24, the processor 24 executes the steps of the anti-face recognition method.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device. For example, the computer program may be divided into units or modules of the berth-status display system provided by the various system embodiments described above.
Those skilled in the art will appreciate that the above description of the terminal device is merely exemplary and not limiting, and that more or fewer components than those described above may be included, or certain components may be combined, or different components may be included, such as input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal equipment and connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory mainly comprises a storage program area and a storage data area, wherein the storage program area can store an operating system, application programs (such as an information acquisition template display function, a product information publishing function and the like) required by at least one function and the like; the storage data area may store data created according to the use of the berth-state display system (e.g., product information acquisition templates corresponding to different product types, product information that needs to be issued by different product providers, etc.), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The terminal device 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, all or part of the modules/units in the system according to the above embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium and used by a processor to implement the functions of the system embodiments. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like.
The human face anti-recognition method provided by the embodiment of the invention obtains the human face image to be recognized in front of the display screen; extracting regional characteristic information in the face image; matching the regional characteristic information with a preset human face characteristic database; confirming the identity information of a face image to be recognized; acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information; therefore, the face image information can be protected in the process of face recognition of people, and the information safety of people is guaranteed.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A human face anti-recognition method is applied to computer equipment with a display screen, and is characterized by comprising the following steps:
acquiring a face image to be recognized in front of the display screen;
extracting regional characteristic information in the face image;
matching the regional characteristic information with a preset human face characteristic database;
acquiring standard face information matched with the regional characteristic information of the face image in a face characteristic database, and confirming the identity information of the face image to be recognized when the matching degree of the standard face information and the regional characteristic information of the face image is greater than a preset matching degree;
the method comprises the steps of obtaining regional characteristic information of a confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information.
2. The method for anti-human face recognition according to claim 1, wherein the method for forming the human face feature database comprises the following specific steps:
acquiring the feature information of the face region in the face picture library;
integrating the human face characteristic points of the human face region characteristic information to form a corresponding characteristic human face image in the human face picture library;
and acquiring the characteristic face images in all the face picture libraries in a face database to form the face characteristic database.
3. The method for anti-human face recognition according to claim 2, wherein the step of obtaining the standard human face information comprises:
acquiring a characteristic face image in a face characteristic database;
detecting the characteristic face image through a cascade multitask convolution neural network model to obtain face characteristic points of the characteristic face image;
carrying out approximate transformation on the characteristic face image based on the facial feature points of the characteristic face image and the facial feature points of a standard image to obtain the standard face image with the standard face information; and preprocessing the standard face image by random brightness, contrast and saturation to obtain the standard face information.
4. The anti-human face recognition method according to any one of claims 1 to 3, further comprising: before the face image to be recognized in front of the display screen is obtained, detecting that a camera of the display screen on the computer equipment is in an open state, and adjusting the brightness of the display screen to a maximum value.
5. A human face anti-recognition system is applied to a computer device with a display screen, and comprises:
the first acquisition module is used for acquiring a face image to be recognized in front of the display screen;
the extraction module is used for extracting regional characteristic information in the face image;
the matching module is used for matching the region characteristic information with a preset human face characteristic database;
the second acquisition module is used for acquiring standard face information matched with the regional characteristic information of the face image in the face characteristic database, and confirming the identity information of the face image to be recognized when the matching degree of the standard face information and the regional characteristic information of the face image is greater than the preset matching degree;
the detection and identification module is used for acquiring regional characteristic information of the confirmed face image, replacing the regional characteristic information to generate target face information, identifying the target face information by using detection equipment, and storing the target face information when the detection equipment cannot identify the target face information.
6. The anti-face recognition system as claimed in claim 5, wherein the anti-face recognition system further comprises: and the detection adjusting module is used for detecting that a camera of a display screen on the computer equipment is in an opening state and adjusting the brightness of the display screen to a maximum value.
7. The system according to claim 6, further comprising means for forming the face feature database, wherein the means for forming the face feature database specifically comprises:
the third acquisition module is used for acquiring the feature information of the face area in the face picture library;
the integration module is used for integrating the human face characteristic points of the human face region characteristic information to form a corresponding characteristic human face image in the human face picture library;
and the fourth acquisition module is used for acquiring the characteristic face images in all the face picture libraries in the face database to form the face characteristic database.
8. The system according to claim 7, further comprising a device for acquiring the standard face information, wherein the device for acquiring the standard face information specifically comprises:
the fifth acquisition module is used for acquiring a characteristic face image in the face characteristic database;
the detection module is used for detecting the characteristic face image through a cascade multitask convolution neural network model so as to obtain facial characteristic points of the characteristic face image;
the image processing module is used for carrying out approximate transformation on the characteristic face image based on the facial feature points of the characteristic face image and the facial feature points of a standard image to obtain the standard face image with the standard face information; and preprocessing the standard face image by random brightness, contrast and saturation to obtain the standard face information.
9. A computer arrangement comprising a display, a memory, a processor and a computer program, wherein the memory has stored therein the computer program which, when executed by the processor, causes the processor to carry out the steps of the anti-face recognition method according to any one of claims 1 to 4.
10. A readable storage medium, having stored thereon a computer program which, when executed by a processor, causes the processor to carry out the steps of the anti-face recognition method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010964608.1A CN112101200A (en) | 2020-09-15 | 2020-09-15 | Human face anti-recognition method, system, computer equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010964608.1A CN112101200A (en) | 2020-09-15 | 2020-09-15 | Human face anti-recognition method, system, computer equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112101200A true CN112101200A (en) | 2020-12-18 |
Family
ID=73752395
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010964608.1A Pending CN112101200A (en) | 2020-09-15 | 2020-09-15 | Human face anti-recognition method, system, computer equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112101200A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112906571A (en) * | 2021-02-20 | 2021-06-04 | 成都新希望金融信息有限公司 | Living body identification method and device and electronic equipment |
| CN114530033A (en) * | 2022-02-18 | 2022-05-24 | 平安国际智慧城市科技股份有限公司 | Eye screen distance warning method, device, equipment and storage medium based on face recognition |
| CN116778487A (en) * | 2023-08-11 | 2023-09-19 | 四川汉唐云分布式存储技术有限公司 | System and method for adding unique identifier to personal head at monitoring interface |
| CN117456589A (en) * | 2023-12-22 | 2024-01-26 | 珠海早安科技有限公司 | Human face identification access control method based on AI and access control system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109726625A (en) * | 2018-08-13 | 2019-05-07 | 平安科技（深圳）有限公司 | Anti- face identification method, device, terminal device and storage medium |
| CN111160202A (en) * | 2019-12-20 | 2020-05-15 | 万翼科技有限公司 | AR equipment-based identity verification method, AR equipment-based identity verification device, AR equipment-based identity verification equipment and storage medium |
| CN111241930A (en) * | 2019-12-30 | 2020-06-05 | 航天信息股份有限公司 | Method and system for face recognition |
| CN111626132A (en) * | 2020-04-27 | 2020-09-04 | 上海携程国际旅行社有限公司 | Model generation method, face recognition method, system, device and medium |
| CN111626161A (en) * | 2020-05-15 | 2020-09-04 | Oppo（重庆）智能科技有限公司 | Face recognition method and device, terminal and readable storage medium |
-
2020
- 2020-09-15 CN CN202010964608.1A patent/CN112101200A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109726625A (en) * | 2018-08-13 | 2019-05-07 | 平安科技（深圳）有限公司 | Anti- face identification method, device, terminal device and storage medium |
| CN111160202A (en) * | 2019-12-20 | 2020-05-15 | 万翼科技有限公司 | AR equipment-based identity verification method, AR equipment-based identity verification device, AR equipment-based identity verification equipment and storage medium |
| CN111241930A (en) * | 2019-12-30 | 2020-06-05 | 航天信息股份有限公司 | Method and system for face recognition |
| CN111626132A (en) * | 2020-04-27 | 2020-09-04 | 上海携程国际旅行社有限公司 | Model generation method, face recognition method, system, device and medium |
| CN111626161A (en) * | 2020-05-15 | 2020-09-04 | Oppo（重庆）智能科技有限公司 | Face recognition method and device, terminal and readable storage medium |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112906571A (en) * | 2021-02-20 | 2021-06-04 | 成都新希望金融信息有限公司 | Living body identification method and device and electronic equipment |
| CN112906571B (en) * | 2021-02-20 | 2023-09-05 | 成都新希望金融信息有限公司 | Living body identification method and device and electronic equipment |
| CN114530033A (en) * | 2022-02-18 | 2022-05-24 | 平安国际智慧城市科技股份有限公司 | Eye screen distance warning method, device, equipment and storage medium based on face recognition |
| CN116778487A (en) * | 2023-08-11 | 2023-09-19 | 四川汉唐云分布式存储技术有限公司 | System and method for adding unique identifier to personal head at monitoring interface |
| CN117456589A (en) * | 2023-12-22 | 2024-01-26 | 珠海早安科技有限公司 | Human face identification access control method based on AI and access control system |
| CN117456589B (en) * | 2023-12-22 | 2024-04-26 | 珠海早安科技有限公司 | Human face identification access control method based on AI and access control system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112101200A (en) | Human face anti-recognition method, system, computer equipment and readable storage medium | |
| CN110866466B (en) | Face recognition method, device, storage medium and server | |
| CN110163096B (en) | Person identification method, person identification device, electronic equipment and computer readable medium | |
| JP2012238121A (en) | Image recognition device, control method for the device, and program | |
| EP3783524A1 (en) | Authentication method and apparatus, and electronic device, computer program, and storage medium | |
| CN110991231B (en) | Living body detection method and device, server and face recognition equipment | |
| EP3869448A1 (en) | Iris authentication device, iris authentication method, and recording medium | |
| CN113642639B (en) | Living body detection method, living body detection device, living body detection equipment and storage medium | |
| WO2022077139A1 (en) | Face recognition method and device and readable storage medium | |
| CN111881740A (en) | Face recognition method, face recognition device, electronic equipment and medium | |
| Gunawan et al. | Performance Evaluation of Automatic Number Plate Recognition on Android Smartphone Platform. | |
| CN114861241A (en) | Anti-peeping screen method based on intelligent detection and related equipment thereof | |
| US9286707B1 (en) | Removing transient objects to synthesize an unobstructed image | |
| CN111783677B (en) | Face recognition method, device, server and computer readable medium | |
| CN113705366A (en) | Personnel management system identity identification method and device and terminal equipment | |
| CN112395580A (en) | Authentication method, device, system, storage medium and computer equipment | |
| CN111931148A (en) | Image processing method and device and electronic equipment | |
| CN108270973B (en) | Photographing processing method, mobile terminal and computer readable storage medium | |
| CN116881967A (en) | Privacy protection method, device and equipment | |
| CN108875472B (en) | Image acquisition device and face identity verification method based on image acquisition device | |
| CN112766235B (en) | Face recognition method, apparatus, device, storage medium and computer program product | |
| CN111221803B (en) | Feature library management method and coprocessor | |
| CN109726625B (en) | Face recognition method, device, terminal equipment and storage medium | |
| CN113673374A (en) | Face recognition method, device and equipment | |
| CN111860272A (en) | Image processing method, chip and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |