CN112417998A - Method and device for acquiring living body face image, medium and equipment - Google Patents

Method and device for acquiring living body face image, medium and equipment Download PDF

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Publication number
CN112417998A
CN112417998A CN202011212451.3A CN202011212451A CN112417998A CN 112417998 A CN112417998 A CN 112417998A CN 202011212451 A CN202011212451 A CN 202011212451A CN 112417998 A CN112417998 A CN 112417998A
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face
face image
image
living body
effective
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何巍
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Aisino Corp
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Aisino Corp
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/168Feature extraction; Face representation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172Classification, e.g. identification
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/40Spoof detection, e.g. liveness detection
    • G06V40/45Detection of the body part being alive

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  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Collating Specific Patterns (AREA)
  • Image Processing (AREA)

Abstract

The disclosure relates to a method, a device, a medium and equipment for acquiring a human face image of a living body. The method comprises the following steps: acquiring an original image; detecting a human face feature point in the original image; drawing a face rectangular frame according to the feature points of the detected face; if a plurality of face rectangular frames are drawn, determining the face rectangular frame with the largest area as an effective face image; and intercepting a living body face image corresponding to the effective face image from the original image. The scheme provides a face image acquisition method under a multi-user background environment, which can accurately acquire a face image of a current user, eliminate the face image as interference and enable the user identity to be more accurately confirmed.

Description

Method and device for acquiring living body face image, medium and equipment
Technical Field
The present disclosure relates to the field of computer image processing, and in particular, to a method, an apparatus, a medium, and a device for acquiring a human face image.
Background
In a biometric system, in order to prevent malicious forgery and theft of the biometric characteristics of others for identity authentication, the biometric system needs to have a liveness detection function, i.e., to determine whether the submitted biometric characteristics are from a living individual. As the face recognition technology becomes mature, the commercial application becomes wider, but the face is easily copied by using the modes of photos, videos and the like, so that the counterfeit of the face of the user is an important threat to the safety of the face recognition and authentication system. At present, living body detection methods based on dynamic video face detection, thermal infrared and visible light face correlation and the like have made certain progress.
At present, identity authentication based on face recognition is widely applied to real-name authentication, a user detects and recognizes a face through a client, an acquired face image is transmitted to a background server, and the identity of the user is authenticated by adopting a face recognition algorithm.
In the process of acquiring the face image by the user, if a plurality of faces exist in the background image, the real face passing through the living body detection needs to be eliminated as an interference face image, and the unique and complete face image is transmitted to the background server after the image processing.
Disclosure of Invention
The invention aims to provide a method, a device, a medium and equipment for reliably acquiring a living human face image.
In order to achieve the above object, the present disclosure provides a method for acquiring a face image of a living body, the method including:
acquiring an original image;
detecting a human face feature point in the original image;
drawing a face rectangular frame according to the feature points of the detected face;
if a plurality of face rectangular frames are drawn, determining the face rectangular frame with the largest area as an effective face image;
and intercepting a living body face image corresponding to the effective face image from the original image.
Optionally, detecting a human face feature point in the original image comprises:
detecting one or more of the following human face feature points in the original image using a haar classifier: eyebrow, eye orbit, nose, mouth, face.
Optionally, drawing a face rectangular frame according to the feature points of the detected face, including:
and determining the left edge and the right edge of the face rectangular frame according to the face edge by taking the height of the highest point of the eyebrow as the height of the upper edge of the face rectangular frame and the height of the lowest point of the chin as the height of the lower edge of the face rectangular frame.
Optionally, intercepting a living body face image corresponding to the effective face image from the original image includes:
taking the lower edge of the effective face image as the lower edge of the living body face image;
taking the left edge of the effective face image as the left edge of the living body face image;
taking the right edge of the effective face image as the right edge of the living body face image;
and taking 1.5 times of the height of the effective face image as the height of the living body face image.
Optionally, intercepting a living body face image corresponding to the effective face image from the original image includes:
and rotating the original image by 90 degrees, and then capturing the living body face image corresponding to the effective face image.
Optionally, the method further comprises:
outputting an action instruction;
within a preset time after the action instruction is output, acquiring the change of the human face characteristic points in the effective human face image;
determining whether the change corresponds to the action command,
intercepting a living body face image corresponding to the effective face image from the original image, wherein the living body face image comprises the following steps:
and if the change is judged to accord with the action instruction, intercepting a living body face image corresponding to the effective face image from the original image.
The present disclosure further provides an apparatus for acquiring a face image of a living body, wherein the apparatus includes:
the first acquisition module is used for acquiring an original image;
the detection module is used for detecting face characteristic points in the original image;
the drawing module is used for drawing a face rectangular frame according to the feature points of the detected face;
the determining module is used for determining the face rectangular frame with the largest area as an effective face image if a plurality of face rectangular frames are drawn;
and the intercepting module is used for intercepting the living body face image corresponding to the effective face image from the original image.
Optionally, the detection module includes:
a detection sub-module for detecting one or more of the following facial feature points in the original image using a haar classifier: eyebrow, eye orbit, nose, mouth, face.
The present disclosure also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described method provided by the present disclosure.
The present disclosure also provides an electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the above-described method provided by the present disclosure.
Through the technical scheme, if a plurality of face rectangular frames are drawn, the face rectangular frame with the largest area is determined as the effective face image. The scheme provides a face image acquisition method under a multi-user background environment, which can accurately acquire a face image of a current user, eliminate the face image as interference and enable the user identity to be more accurately confirmed.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
FIG. 1 is a flow chart of a method for acquiring a live face image according to an exemplary embodiment;
FIG. 2 is a schematic diagram of determining valid face images provided by an exemplary embodiment;
FIG. 3 is a schematic diagram of drawing a rectangular box of a face according to an exemplary embodiment;
FIG. 4 is a schematic diagram of an intercepted live face image provided by an exemplary embodiment;
FIG. 5 is a schematic diagram of an intercepted live face image applied to an iOS client according to an exemplary embodiment;
FIG. 6 is a block diagram of an apparatus for acquiring a face image of a living subject according to an exemplary embodiment;
FIG. 7 is a block diagram of an electronic device, shown in an example embodiment.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flowchart of a method for acquiring a face image of a living body according to an exemplary embodiment. As shown in fig. 1, the method may include the following steps.
Step S101, an original image is acquired.
The original image may be an image directly acquired by a camera. For example, a user may perform face live detection through a terminal (e.g., a mobile phone or a PC), and record a video stream for 3 to 5 seconds through a front camera.
The iOS terminal may output a frame image using the AVCaptureVideoDataOutput. Setting video stream parameters as kCVPixelBuxelPixelFormatTypeKey and AVMediaTypeVideo, and calling CaptureOutputdinOutputOutputSampleBuffer to obtain pixel points of the frame image.
In step S102, a face feature point is detected in the original image.
The face feature points refer to pixel points in an image indicating a specific organ in a face.
For example, one or more of the following facial feature points may be detected in the raw image using a Haar classifier in OpenCV: eyebrow, eye orbit, nose, mouth, face.
And step S103, drawing a face rectangular frame according to the feature points of the detected face. The drawn face rectangle may include individual face feature points.
And step S104, if a plurality of face rectangular frames are drawn, determining the face rectangular frame with the largest area as an effective face image.
In the case that a plurality of persons enter the range of the camera at the same time, the face characteristic points of the plurality of persons are detected, so that a plurality of face rectangular frames are drawn. Since the user usually stands at the forefront of the camera and is closest to the camera when verifying the identity of the user, the rectangular frame of the drawn face should be the largest. The rest face rectangular frames except the largest face rectangular frame can be excluded.
Fig. 2 is a schematic diagram for determining a valid face image according to an exemplary embodiment. In fig. 2, the face rectangular box a with the largest area may be determined as a valid face image.
And step S105, intercepting a living body face image corresponding to the effective face image from the original image.
Simply, the effective face image can be directly used as the corresponding living body face image, or the effective face image can be used as the corresponding living body face image after being appropriately expanded outwards.
Through the technical scheme, if a plurality of face rectangular frames are drawn, the face rectangular frame with the largest area is determined as the effective face image. The scheme provides a face image acquisition method under a multi-user background environment, which can accurately acquire a face image of a current user, eliminate the face image as interference and enable the user identity to be more accurately confirmed.
In still another embodiment, on the basis of fig. 1, the step of drawing a face rectangular frame according to the feature points of the detected face (step S103) may include: and determining the left edge and the right edge of the face rectangular frame according to the face edge by taking the height of the highest point of the eyebrow as the height of the upper edge of the face rectangular frame and the height of the lowest point of the chin as the height of the lower edge of the face rectangular frame.
Fig. 3 is a schematic diagram for drawing a face rectangle according to an exemplary embodiment. Therefore, on the basis of including effective human face characteristic points, the area of the human face rectangular frame is greatly reduced, the calculation amount is small, and the calculation speed is high.
In still another embodiment, on the basis of fig. 1, the step of intercepting the living body face image corresponding to the valid face image in the original image (step S105) may include:
taking the lower edge of the effective face image as the lower edge of the living body face image; taking the left edge of the effective face image as the left edge of the living body face image; taking the right edge of the effective face image as the right edge of the living body face image; and taking 1.5 times of the height of the effective face image as the height of the living body face image.
Fig. 4 is a schematic diagram of intercepting a live face image according to an exemplary embodiment. As shown in fig. 4, the left rectangular frame is the effective face image, and the right rectangular frame is the living face image. The effective face image reaches the top of the eyebrow from the chin and has a height L. The living body face image was 1.5L in height from the chin up. The left and right edges are unchanged. As can be seen from fig. 4, the edge at the chin is not changed, and 1.5 times of the height of the effective face image is used as the height of the living face image, so that the obtained living face image is suitable for the face proportion of most people, and the area of the output living face image is small on the basis of including the effective face feature points, so that the calculation amount is small during the later-stage matching, and the calculation speed is high.
In still another embodiment, the step of intercepting the living body face image corresponding to the valid face image in the original image (step S105) may include: and rotating the original image by 90 degrees, and then cutting out the living body face image corresponding to the effective face image.
Because the face image that iOS acquiesces and shoots is horizontal, can rotate 90 degrees earlier the original image that obtains, make the face be vertical, according to the embodiment of the last: taking the lower edge of the effective face image as the lower edge of the living body face image; taking the left edge of the effective face image as the left edge of the living body face image; taking the right edge of the effective face image as the right edge of the living body face image; and intercepting the corresponding living body face image by taking 1.5 times of the height of the effective face image as the height of the living body face image.
Fig. 5 is a schematic diagram of an intercepted live face image applied to an iOS client according to an exemplary embodiment. According to the coordinates of four points of the face frame rectangle, the living body face image to be intercepted can be determined as follows:
the horizontal coordinate of the upper left corner of the rectangular frame of the living body face image is equal to the vertical coordinate of the top edge of the rectangular frame of the effective face image, and the width of the rectangular frame of the effective face image is 2;
the ordinate of the upper left corner of the rectangular frame of the living body face image is equal to the abscissa of the left edge of the rectangular frame of the effective face image;
the width of the rectangular frame of the living body face image is equal to the width of the rectangular frame of the effective face image multiplied by 1.5;
and the height of the rectangular frame of the living face image is equal to the height of the rectangular frame of the effective face image.
And then, the CGImageCreateWithImageInRect can be called, and the living body face image is used as a final image and is sent to the server side to be used as the next face function application.
In this embodiment, the method for intercepting the living body face image according to the effective face image is suitable for the iOS terminal.
To perform liveness verification, the client may also be required to make an instructed action to verify. In a further embodiment, the method further comprises the steps of:
outputting an action instruction; within a preset time after the action instruction is output, acquiring the change of the human face characteristic points in the effective human face image; and judging whether the change accords with the action command.
Also, in this embodiment, the step of cutting out the living body face image corresponding to the valid face image in the original image (step S105) may include: and if the change is judged to accord with the action command, intercepting the living body face image corresponding to the effective face image from the original image.
The terminal can randomly output action instructions (such as blinking, opening mouth, closing mouth, shaking head, nodding head and the like), the time of 15 seconds is limited, the coordinate change of the feature points of the corresponding parts is judged according to the effective face image acquired within 15 seconds, whether the output action instructions are met is judged, and therefore whether the face is a living face is judged.
In the embodiment, whether the current image is the living body image of the user can be judged by indicating the user to execute the corresponding action, so that the occurrence of malicious user identity authentication through a pre-prepared photo is avoided, and the benefit of the user is guaranteed.
Fig. 6 is a block diagram of an apparatus for acquiring a face image of a living body according to an exemplary embodiment. As shown in fig. 6, the apparatus 600 for acquiring a face image of a living body may include a first acquisition module 601, a detection module 602, a rendering module 603, a determination module 604, and a truncation module 605.
The first acquiring module 601 is used for acquiring an original image.
The detection module 602 is configured to detect a face feature point in an original image.
The drawing module 603 is configured to draw a face rectangular frame according to the feature points of the detected face.
The determining module 604 is configured to determine a face rectangular frame with the largest area as an effective face image if a plurality of face rectangular frames are drawn.
The intercepting module 605 is configured to intercept a living body face image corresponding to the valid face image in the original image.
Optionally, the detection module 602 may include a detection sub-module.
The detection sub-module is for detecting one or more of the following facial feature points in the original image using a haar classifier: eyebrow, eye orbit, nose, mouth, face.
Optionally, the rendering module 603 may include a determination sub-module.
The determining submodule is used for determining the left edge and the right edge of the face rectangular frame according to the face edge by taking the height of the highest point of the eyebrow as the height of the upper edge of the face rectangular frame and taking the height of the lowest point of the chin as the height of the lower edge of the face rectangular frame.
Optionally, the truncation module 605 includes a first truncation sub-module.
The first truncation submodule is used for taking the lower edge of the effective face image as the lower edge of the living body face image; taking the left edge of the effective face image as the left edge of the living body face image; taking the right edge of the effective face image as the right edge of the living body face image; and taking 1.5 times of the height of the effective face image as the height of the living body face image.
Optionally, the intercept module 605 comprises a second intercept module.
And the second intercepting submodule is used for intercepting the living body face image corresponding to the effective face image after the original image is rotated by 90 degrees.
Optionally, the apparatus 600 for acquiring a face image of a living body may further include an output module, a second acquisition module, and a determination module.
The output module is used for outputting an action instruction
The second acquisition module is used for acquiring the change of the human face characteristic points in the effective human face image within a preset time after the action instruction is output.
The judging module is used for judging whether the change accords with the action instruction.
In this embodiment, the truncation module 605 includes a third truncation sub-module.
And the third intercepting submodule is used for intercepting the living body face image corresponding to the effective face image from the original image if the change is judged to accord with the action instruction.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Through the technical scheme, if a plurality of face rectangular frames are drawn, the face rectangular frame with the largest area is determined as the effective face image. The scheme provides a face image acquisition method under a multi-user background environment, which can accurately acquire a face image of a current user, eliminate the face image as interference and enable the user identity to be more accurately confirmed.
The present disclosure also provides an electronic device comprising a memory and a processor.
The memory has a computer program stored thereon; the processor is used for executing the computer program in the memory to realize the steps of the method for acquiring the living human face image.
Fig. 7 is a block diagram of an electronic device 700, shown in an exemplary embodiment. As shown in fig. 7, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input/output (I/O) interface 704, and a communication component 705.
The processor 701 is configured to control the overall operation of the electronic device 700, so as to complete all or part of the steps in the above-mentioned method for acquiring a living human face image. The memory 702 is used to store various types of data to support operation at the electronic device 700, such as instructions for any application or method operating on the electronic device 700 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 702 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia components 703 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 702 or transmitted through the communication component 705. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 704 provides an interface between the processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, which is not limited herein. The corresponding communication component 705 may thus include: Wi-Fi module, Bluetooth module, NFC module, etc.
In an exemplary embodiment, the electronic Device 700 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used for executing the above-mentioned method for acquiring the living human face image.
In another exemplary embodiment, there is also provided a computer-readable storage medium including program instructions which, when executed by a processor, implement the steps of the above-described method for acquiring a face image of a living body. For example, the computer readable storage medium may be the memory 702 described above including program instructions executable by the processor 701 of the electronic device 700 to perform the above-described method of acquiring a live face image.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, various possible combinations will not be separately described in this disclosure.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.

Claims (10)

1. A method for acquiring a human face image of a living body is characterized by comprising the following steps:
acquiring an original image;
detecting a human face feature point in the original image;
drawing a face rectangular frame according to the feature points of the detected face;
if a plurality of face rectangular frames are drawn, determining the face rectangular frame with the largest area as an effective face image;
and intercepting a living body face image corresponding to the effective face image from the original image.
2. The method of claim 1, wherein detecting human face feature points in the original image comprises:
detecting one or more of the following human face feature points in the original image using a haar classifier: eyebrow, eye orbit, nose, mouth, face.
3. The method of claim 1, wherein drawing a face rectangle according to the feature points of the detected face comprises:
and determining the left edge and the right edge of the face rectangular frame according to the face edge by taking the height of the highest point of the eyebrow as the height of the upper edge of the face rectangular frame and the height of the lowest point of the chin as the height of the lower edge of the face rectangular frame.
4. The method of claim 3, wherein intercepting the live face image corresponding to the valid face image in the original image comprises:
taking the lower edge of the effective face image as the lower edge of the living body face image;
taking the left edge of the effective face image as the left edge of the living body face image;
taking the right edge of the effective face image as the right edge of the living body face image;
and taking 1.5 times of the height of the effective face image as the height of the living body face image.
5. The method of claim 1, wherein intercepting a live face image corresponding to the valid face image in the original image comprises:
and rotating the original image by 90 degrees, and then capturing the living body face image corresponding to the effective face image.
6. The method of claim 1, further comprising:
outputting an action instruction;
within a preset time after the action instruction is output, acquiring the change of the human face characteristic points in the effective human face image;
determining whether the change corresponds to the action command,
intercepting a living body face image corresponding to the effective face image from the original image, wherein the living body face image comprises the following steps:
and if the change is judged to accord with the action instruction, intercepting a living body face image corresponding to the effective face image from the original image.
7. An apparatus for acquiring a face image of a living body, the apparatus comprising:
the first acquisition module is used for acquiring an original image;
the detection module is used for detecting face characteristic points in the original image;
the drawing module is used for drawing a face rectangular frame according to the feature points of the detected face;
the determining module is used for determining the face rectangular frame with the largest area as an effective face image if a plurality of face rectangular frames are drawn;
and the intercepting module is used for intercepting the living body face image corresponding to the effective face image from the original image.
8. The apparatus of claim 7, wherein the detection module comprises:
a detection sub-module for detecting one or more of the following facial feature points in the original image using a haar classifier: eyebrow, eye orbit, nose, mouth, face.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
10. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 6.
CN202011212451.3A 2020-11-03 2020-11-03 Method and device for acquiring living body face image, medium and equipment Pending CN112417998A (en)

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CN110097586A (en) * 2019-04-30 2019-08-06 青岛海信网络科技股份有限公司 A kind of Face datection method for tracing and device
CN111178233A (en) * 2019-12-26 2020-05-19 北京天元创新科技有限公司 Identity authentication method and device based on living body authentication

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