WO2019104930A1 - Procédé d'authentification d'identité, dispositif électronique et support d'enregistrement lisible par ordinateur - Google Patents

Procédé d'authentification d'identité, dispositif électronique et support d'enregistrement lisible par ordinateur Download PDF

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Publication number
WO2019104930A1
WO2019104930A1 PCT/CN2018/083075 CN2018083075W WO2019104930A1 WO 2019104930 A1 WO2019104930 A1 WO 2019104930A1 CN 2018083075 W CN2018083075 W CN 2018083075W WO 2019104930 A1 WO2019104930 A1 WO 2019104930A1
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Prior art keywords
verification
face
terminal
user
voiceprint
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PCT/CN2018/083075
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English (en)
Chinese (zh)
Inventor
牛华
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平安科技（深圳）有限公司
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Publication of WO2019104930A1 publication Critical patent/WO2019104930A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • 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
    • 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

Definitions

  • the present application relates to an authentication method, and in particular, to an identity authentication method, an electronic device, and a computer readable storage medium.
  • the purpose of the present application is to provide an identification method, an electronic device, and a computer readable storage medium, thereby further overcoming the problems existing in the prior art to some extent.
  • the application provides an identification method comprising the following steps:
  • Step 01 The second terminal acquires identity card information collected and sent by the first terminal.
  • Step 02 The second terminal verifies the validity of the identity card information, and if the verification passes, proceeds to step 03, and if the verification fails, the reminder returns to the first terminal to re-acquire;
  • Step 03 The second terminal performs face recognition verification on the user, and the face recognition verification performs the comparison verification by collecting the face image of the user and the photo of the ID card avatar. If the verification is passed, the operation proceeds to the next step. By reminding the user to re-create face recognition.
  • an electronic device including a memory and a processor for storing an identity authentication system executed by a processor, the identity authentication system comprising:
  • the ID card information collection module is used to collect the ID card information of the user, including the photo of the ID card and the ID card number, and perform de-texturing processing on the photo of the avatar.
  • the ID card verification module is used to verify the validity of the collected ID card, including whether the ID card validity period is verified and whether the ID card photo is consistent with the photo of the third party identity verification network.
  • the face recognition module includes a face collection sub-module, a face feature positioning sub-module, a face feature extraction sub-module, and a face feature similarity comparison sub-module, and the face collection sub-module is used to collect a photo of the living face of the user.
  • the face feature locating sub-module is used for locating the user's face feature part located in the acquisition frame, and the face feature extraction sub-module is used for feature extraction of the locating feature, and the face feature similarity comparison is used for the extracted person.
  • the face features are compared with the photos of the third-party verification network for similarity.
  • the present application also discloses a computer readable storage medium having an identity authentication system stored therein, the identity authentication system being executable by at least one processor to implement the following steps :
  • Step 01 The second terminal acquires identity card information collected and sent by the first terminal.
  • Step 02 The second terminal verifies the validity of the identity card information, and if the verification passes, proceeds to step 03, and if the verification fails, the reminder returns to the first terminal to re-acquire;
  • Step 03 The second terminal performs face recognition verification on the user, and the face recognition verification performs the comparison verification by collecting the face image of the user and the photo of the ID card avatar. If the verification is passed, the operation proceeds to the next step. By reminding the user to re-create face recognition.
  • the identification method provided by the present application avoids the use of the prior art by combining the third-party identity verification, the face recognition technology, and the voiceprint recognition multiple identification verification methods after collecting the user identification information.
  • the identity card of someone else or the counterfeiting of the customer to handle the business improves the accuracy and security of the user identity verification.
  • FIG. 1 shows a flow chart of an embodiment of the identity authentication method of the present application.
  • FIG. 2 shows a flow chart of still another embodiment of the identity authentication method of the present application.
  • FIG. 3 is a schematic diagram showing the program modules of an embodiment of the identity authentication system of the present application.
  • FIG. 4 is a schematic diagram showing a program module of still another embodiment of the identity authentication system of the present application.
  • FIG. 5 is a schematic diagram of a program module of still another embodiment of the identity authentication system of the present application.
  • FIG. 6 is a schematic diagram of a program module of still another embodiment of the identity authentication system of the present application.
  • FIG. 7 is a schematic diagram showing the hardware architecture of an embodiment of an electronic device of the present application.
  • an identification method including the following steps:
  • Step 01 The second terminal acquires the identity card information collected and sent by the first terminal.
  • the user sends a service request to the second terminal by using the first terminal, and after receiving the request, the second terminal sends an identity verification command to the first terminal, and after receiving the instruction, the first terminal starts the ID card identifier located at the first terminal.
  • the identification device scans the ID card to extract the avatar located on the ID card Photo, ID number information, and de-texturing the avatar photo, sending the processed photo and ID number information to the file server of the first terminal and forming an identification ID code for extracting the photo and information
  • the first terminal sends the identification ID code to the second terminal.
  • the first terminal is a client
  • the second terminal is a client.
  • step 02 the second terminal verifies the validity of the identity card information. If the verification succeeds, the process proceeds to step 03. If the verification fails, the first terminal re-acquires.
  • the second terminal obtains the user information corresponding to the ID card from the verification network through the interface connected with the third-party identity verification network, and obtains the ID information of the user site from the first terminal by using the ID code, and checks the online information through the third party.
  • the user identity information determines whether the user's ID card is within the validity period, and compares the photo of the user on the online check with the photo of the collected ID card avatar. If the similarity of the two photos exceeds the first threshold, the verification passes, if low At the first threshold, the verification fails, wherein the first threshold may be 70, and the first threshold may be obtained by statistical analysis of historical similarity values, wherein the third-party identity verification network may be public security network or authenticated by the Ministry of Public Security. Third-party identity information network.
  • Step 03 The second terminal performs face recognition verification on the user, and the face recognition verification performs the comparison verification by collecting the user face image and the ID card avatar photo. If the verification is passed, the next operation is performed, and if the verification is not performed, By reminding the user to re-create face recognition.
  • the second terminal After the ID card is verified, the second terminal starts the face recognition module to perform face recognition verification on the user, and the second terminal sends an instruction to start the Gao Paiyi to the first terminal. After receiving the instruction, the first terminal turns on the Gao Paiyi. And the user is prompted to perform text and voice operations on the first terminal interface, and the user performs the shooting of the live face image at the prompt. After the shooting is completed, the photo is transmitted back to the second terminal, and the face recognition module of the second terminal will The face image is compared with the third-party verification network user avatar. If the similarity between the two comparison results exceeds the second threshold, the verification is passed. If the similarity is lower than the second threshold, the verification fails. The second terminal reminds the user to perform the second face recognition verification. If the two terminals do not pass, the user is reminded to hold the valid ID to go to the counter for face-to-face check.
  • the second threshold may be obtained by statistical analysis of historical data. Preferably, the second threshold is 60.
  • the image acquisition of the face image includes: the second terminal sends an image acquisition instruction to the first terminal through the sip server, and the first terminal starts the high-speed image to perform image acquisition, and the high-speed device connects to the first terminal through the USB interface, and the agent sends the detection through the USB interface.
  • the device detects the sub-module to the user end, and the device detection sub-module detects the performance of the high-shooter in various states, including the high-shooter capable of starting the shooting control, whether the angle adjustment of the camera is flexible, and whether the picture transmission channel is turned on or the like. Adjust the shooting mode and shooting parameters of the Gao Paiyi, and display the above modes and parameters on the display interface of the agent.
  • the seat can set the above parameters as needed.
  • the seat can remotely control the Gao Paiyi to shoot in the night or day mode, as well as adjust the shooting angle of the camera of the Gao Paiyi, shooting pixels and other parameters.
  • the captured image is processed, the captured image is sent to the image processing module, the image is named and compressed, and the brightness, resolution, contrast and other parameters of the captured image are adjusted, and according to the preset
  • the compression ratio compresses the original image into a thumbnail.
  • the processed image is sent to the second terminal, and the client stores the original image taken by the Gao Paiyi and the compressed thumbnail image on the middle storage module, and sends it to the agent terminal in a circular queue through the communication module.
  • the second terminal After receiving the image data, the second terminal converts the image data into a displayable format according to the data conversion protocol, and classifies and integrates the converted image by category, groups the same type of images and selects an image satisfying the condition, if the image is If the pixel, the definition, the brightness, the shooting angle, etc. satisfy the requirement, the completion command is sent to the first terminal. If one of the above parameters does not meet the requirement, the re-acquisition command is sent to the first terminal, and the first terminal starts to shoot again. .
  • the face recognition comparison includes face acquisition, face feature location, face feature extraction and face feature similarity comparison.
  • the face collection includes marking the face coordinates and detecting whether there is a human face, evaluating the shooting quality, and screenshotting the face image. Specifically, including marking the face coordinates after opening the camera and detecting whether there is a face, evaluating the shooting quality, and screening the face. image. It is detected whether a human face can judge whether it has a positive facial features and has a complete facial contour based on the coordinates of the hit and the pre-existing facial features.
  • Evaluating the photographing quality may include a head angle evaluation, a brightness evaluation, and a motion blur evaluation
  • the head angle evaluation includes determining whether the head is up and down, for example, within 15 degrees, the left and right declination is within, for example, 15 degrees, and the rotational declination is, for example, Within 20°, if it is consistent, it is considered to meet the head angle assessment
  • the brightness evaluation includes determining whether the brightness is within, for example, [80,200], if it is met, it is considered to meet the brightness evaluation
  • the dynamic fuzzy evaluation includes judging the fuzzy value. Whether it is less than 0.2, for example, if it is met, it is considered to be in compliance with the dynamic fuzzy assessment.
  • evaluating the quality of the shot may also include determining whether the user wears thick-rimmed glasses, sunglasses, or whether the hair blocks the ears or other facial features.
  • the facial feature localization includes positioning a plurality of features of the human face including the organ, including positioning a plurality of features of the human face including the eyebrows, the eyes, the nose, the mouth, and the like.
  • the facial feature extraction includes extracting a plurality of feature information of each feature according to a preset extraction rule.
  • the face feature similarity comparison includes comparing the extracted feature information with the feature information of the ID card avatar photo and obtaining a second comparison threshold, wherein the face feature may include a length and a slope.
  • the parameters such as the gradation difference represent the three-dimensional size, the oblique direction, the distance from other parts, and the like, and the face feature may be a set of feature information.
  • the facial feature similarity comparison may be to compare the two sets of feature information one by one, and define each feature information to have a certain weight, for example, the weight of the important feature information, and the weight of the secondary feature information is relatively small, and may also be defined. Some feature information is a necessary condition for judging that it must be consistent.
  • an identification method including the following steps:
  • Step 01 The second terminal acquires the identity card information collected and sent by the first terminal.
  • the user sends a service request to the second terminal by using the first terminal, and after receiving the request, the second terminal sends an identity verification command to the first terminal, and after receiving the instruction, the first terminal starts the ID card identifier located at the first terminal.
  • the identification device scans the ID card to extract the avatar located on the ID card Photo, ID number information, and de-texturing the avatar photo, sending the processed photo and ID number information to the file server of the first terminal and forming an identification ID code for extracting the photo and information
  • the first terminal sends the identification ID code to the second terminal.
  • the first terminal is a client
  • the second terminal is a client.
  • step 02 the second terminal verifies the validity of the identity card information. If the verification succeeds, the process proceeds to step 03. If the verification fails, the first terminal re-acquires.
  • the second terminal obtains the user information corresponding to the ID card from the verification network through the interface connected with the third-party identity verification network, and obtains the ID information of the user site from the first terminal by using the ID code, and checks the online information through the third party.
  • the user identity information determines whether the user's ID card is within the validity period, and compares the photo of the user on the online check with the photo of the collected ID card avatar. If the similarity of the two photos exceeds the first threshold, the verification passes, if low At the first threshold, the verification fails, wherein the first threshold may be 70, and the first threshold may be obtained by statistical analysis of historical similarity values, wherein the third-party identity verification network may be public security network or authenticated by the Ministry of Public Security. Third-party identity information network.
  • Step 03 The second terminal performs face recognition verification on the user, and the face recognition verification performs the comparison verification by collecting the user face image and the ID card avatar photo. If the verification is passed, the next operation is performed, and if the verification is not performed, By reminding the user to re-create face recognition.
  • the second terminal After the ID card is verified, the second terminal starts the face recognition module to perform face recognition verification on the user, and the second terminal sends an instruction to start the Gao Paiyi to the first terminal. After receiving the instruction, the first terminal turns on the Gao Paiyi. And the user is prompted to perform text and voice operations on the first terminal interface, and the user performs the shooting of the live face image at the prompt. After the shooting is completed, the photo is transmitted back to the second terminal, and the face recognition module of the second terminal will The face image is compared with the third-party verification network user avatar. If the similarity between the two comparison results exceeds the second threshold, the verification is passed. If the similarity is lower than the second threshold, the verification fails. The second terminal reminds the user to perform the second face recognition verification. If the two terminals do not pass, the user is reminded to hold the valid ID to go to the counter for face-to-face check.
  • the second threshold may be obtained by statistical analysis of historical data. Preferably, the second threshold is 60.
  • the image acquisition of the face image includes: the second terminal sends an image acquisition instruction to the first terminal through the sip server, and the first terminal starts the high-speed image to perform image acquisition, and the high-speed device connects to the first terminal through the USB interface, and the agent sends the detection through the USB interface.
  • the device detects the sub-module to the user end, and the device detection sub-module detects the performance of the high-shooter in various states, including the high-shooter capable of starting the shooting control, whether the angle adjustment of the camera is flexible, and whether the picture transmission channel is turned on or the like. Adjust the shooting mode and shooting parameters of the Gao Paiyi, and display the above modes and parameters on the display interface of the agent.
  • the seat can set the above parameters as needed.
  • the seat can remotely control the Gao Paiyi to shoot in the night or day mode, as well as adjust the shooting angle of the camera of the Gao Paiyi, shooting pixels and other parameters.
  • the captured image is processed, the captured image is sent to the image processing module, the image is named and compressed, and the brightness, resolution, contrast and other parameters of the captured image are adjusted, and according to the preset
  • the compression ratio compresses the original image into a thumbnail.
  • the processed image is sent to the second terminal, and the client stores the original image taken by the Gao Paiyi and the compressed thumbnail image on the middle storage module, and sends it to the agent terminal in a circular queue through the communication module.
  • the second terminal After receiving the image data, the second terminal converts the image data into a displayable format according to the data conversion protocol, and classifies and integrates the converted image by category, groups the same type of images and selects an image satisfying the condition, if the image is If the pixel, the definition, the brightness, the shooting angle, etc. satisfy the requirement, the completion command is sent to the first terminal. If one of the above parameters does not meet the requirement, the re-acquisition command is sent to the first terminal, and the first terminal starts to shoot again. .
  • the face recognition comparison includes face acquisition, face feature location, face feature extraction and face feature similarity comparison.
  • the face collection includes marking the face coordinates and detecting whether there is a human face, evaluating the shooting quality, and screenshotting the face image. Specifically, including marking the face coordinates after opening the camera and detecting whether there is a face, evaluating the shooting quality, and screening the face. image. It is detected whether a human face can judge whether it has a positive facial features and has a complete facial contour according to the coordinates of the hit and the pre-existing range of facial features.
  • Evaluating the photographing quality may include a head angle evaluation, a brightness evaluation, and a motion blur evaluation
  • the head angle evaluation includes determining whether the head is up and down, for example, within 15 degrees, the left and right declination is within, for example, 15 degrees, and the rotational declination is, for example, Within 20°, if it is consistent, it is considered to meet the head angle assessment
  • the brightness evaluation includes determining whether the brightness is within, for example, [80,200], if it is met, it is considered to meet the brightness evaluation
  • the dynamic fuzzy evaluation includes judging the fuzzy value. Whether it is less than 0.2, for example, if it is met, it is considered to be in compliance with the dynamic fuzzy assessment.
  • evaluating the quality of the shot may also include determining whether the user wears thick-rimmed glasses, sunglasses, or whether the hair blocks the ears or other facial features.
  • the facial feature localization includes positioning a plurality of features of the human face including the organ, including positioning a plurality of features of the human face including the eyebrows, the eyes, the nose, the mouth, and the like.
  • the facial feature extraction includes extracting a plurality of feature information of each feature according to a preset extraction rule.
  • the face feature similarity comparison includes comparing the extracted feature information with the feature information of the ID card avatar photo and obtaining a second comparison threshold, wherein the face feature may include a length and a slope.
  • the parameters such as the gradation difference represent the three-dimensional size, the oblique direction, the distance from other parts, and the like, and the face feature may be a set of feature information.
  • the facial feature similarity comparison may be to compare the two sets of feature information one by one, and define each feature information to have a certain weight, for example, the weight of the important feature information, and the weight of the secondary feature information is relatively small, and may also be defined. Some feature information is a necessary condition for judging that it must be consistent.
  • Step 04 The second terminal performs voiceprint identification verification on the user, and if the verification passes, proceeds to the next operation, and if the verification fails, the user is reminded to try again.
  • the second terminal starts the voiceprint recognition module to perform voiceprint recognition verification on the user, and the second terminal sends an instruction for collecting the user audio to the audio collection module of the first terminal, and the first terminal prompts the user to issue a specified voice through voice, and the audio collection module pairs
  • the collected audio is processed and sent to the voiceprint recognition module of the second terminal to extract and compare the voiceprint features, and the second terminal extracts the voiceprint information recorded when the user first performs the business and performs the voiceprint information collected with the collected voiceprint information.
  • the similarity comparison if the similarity is greater than the third threshold, the verification is passed, and if the similarity is less than the third threshold, the verification fails.
  • the second threshold can be obtained by statistical analysis of historical data.
  • an authentication system 20 is illustrated.
  • the identity authentication system 20 is partitioned into one or more program modules, one or more program modules are stored in a storage medium, and Executed by one or more processors to complete the application.
  • a program module as used herein refers to a series of computer program instructions that are capable of performing a particular function. The following description will specifically describe the functions of each program module of this embodiment:
  • the ID card information collection module 201 is configured to collect the ID information of the user, including the photo of the ID card and the ID card number, and perform de-texturing processing on the photo of the avatar.
  • the ID card verification module 202 is configured to verify the validity of the collected ID card, including whether the ID card validity period is verified and whether the ID card photo is consistent with the photo of the third party identity verification network.
  • the face recognition module 203 includes a face collection sub-module 2031, a face feature locating sub-module 2032, a face feature extraction sub-module 2033, and a face feature similarity comparison sub-module 2034.
  • the face collection sub-module is used to collect users. The photograph of the living face, the face feature locating sub-module is used for locating the user's face feature part located in the collection frame, and the face feature extraction sub-module is used for feature extraction of the locating feature, and the face feature similarity comparison is used. The similarity comparison is performed on the extracted face features and the photos of the third party verification network.
  • the identity authentication system further includes a voiceprint recognition module 204, including an audio collection sub-module 2041, a voiceprint feature extraction sub-module 2042, and a voiceprint comparison sub-module 2043.
  • the audio collection sub-module is used to collect and denoise the user's voice
  • the voiceprint feature extraction sub-module is used to extract the voiceprint feature of the collected audio
  • the voiceprint comparison sub-module is used to collect the sound.
  • the voiceprint feature is compared with the user's archived voiceprint features for similarity verification.
  • the embodiment provides an electronic device. It is a schematic diagram of the hardware architecture of an embodiment of the electronic device of the present application.
  • the electronic device 2 is an apparatus capable of automatically performing numerical calculation and/or information processing in accordance with an instruction set or stored in advance.
  • it can be a smartphone, a tablet, a laptop, a desktop computer, a rack server, a blade server, a tower server, or a rack server (including a stand-alone server, or a server cluster composed of multiple servers).
  • the electronic device 2 includes at least, but not limited to, a memory 21, a processor 22, a network interface 23, an ID card identifier 24, a Gao Paiometer 25, and an identification system 20 that are communicably coupled to each other through a system bus. . among them:
  • the memory 21 includes at least one type of computer readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), a random access memory (RAM), Static Random Access Memory (SRAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, and the like.
  • the memory 21 may be an internal storage module of the electronic device 2, such as a hard disk or a memory of the electronic device 2.
  • the memory 21 may also be an external storage device of the electronic device 2, such as a plug-in hard disk equipped on the electronic device 2, a smart memory card (SMC), and a secure digital device. (Secure Digital, SD) card, flash card, etc.
  • the memory 21 can also include both the internal storage module of the electronic device 2 and its external storage device.
  • the memory 21 is generally used to store an operating system installed in the electronic device 2 and various types of application software, such as program codes of the identity authentication system 20. Further, the memory 21 can also be used to temporarily store various types of data that have been output or are to be output.
  • the processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
  • the processor 22 is typically used to control the overall operation of the electronic device 2, such as performing control and processing associated with data interaction or communication with the electronic device 2.
  • the processor 22 is configured to run program code or process data stored in the memory 21, such as running the identity authentication system 20 or the like.
  • the network interface 23 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the electronic device 2 and other electronic devices.
  • the network interface 23 is configured to connect the electronic device 2 to an external terminal through a network, establish a data transmission channel, a communication connection, and the like between the electronic device 2 and an external terminal.
  • the network may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, or a 5G network.
  • Wireless or wired networks such as network, Bluetooth, Wi-Fi, etc.
  • Figure 7 only shows the electronic device with components 20-25, but it should be understood that not all illustrated components may be implemented and that more or fewer components may be implemented instead.
  • the identity authentication system 20 stored in the memory 21 can also be divided into one or more program modules, the one or more program modules being stored in the memory 21 and composed of one or more
  • the processor this embodiment is processor 22
  • FIG. 3 shows a schematic diagram of a program module of the first embodiment of the identity authentication system 20.
  • the identity-based authentication system 20 can be divided into an identity card information collection module 201 and an identity card verification module 202.
  • the program module referred to in the present application refers to a series of computer program instruction segments capable of performing a specific function. The specific functions of the program modules 201-203 are described in detail in the third embodiment, and details are not described herein again.
  • the ID card identification device 24 is configured to be connected to the identity information collection module 201, and collects ID information stored by the user, such as pre-stored information in the chip of the second generation ID card.
  • the high beater 25 is configured to be activated and deactivated by the authentication module 202 to collect a face image of the operating terminal device.
  • the Gao Paiyi 25 can be connected to the electronic device 2 of the user terminal through the USB interface.
  • the user adjusts the shooting angle of the two cameras of the Gao Paiyi according to the actual shooting angle or the control module that sends the command to the user terminal through the command port to control the Gao Paiyi. Different operations enable remote control of the Gao Paiyi.
  • the Gao Paiyi takes a good photo and sends it back to the seat.
  • the seat selects whether to re-adjust the shooting parameters of the Gao Paiyi according to the shooting effect of the photo to obtain the photo that meets the requirements.
  • a flash 26 is also included that is configured to be activated and deactivated by the shooting adjustment subroutine and adjusted in brightness.
  • the embodiment provides a computer readable storage medium on which the identity authentication system 20 is stored, and the identity authentication system 20 is implemented by one or more processors to implement the above identity authentication method or electronic device. Operation.

Abstract

L'invention concerne un procédé d'authentification d'identité, un dispositif électronique et un support d'enregistrement lisible par ordinateur. Le procédé comprend les étapes suivantes : étape 01, un second terminal acquiert des informations de carte d'identité collectées et envoyées par un premier terminal; étape 02, le second terminal vérifie la validité des informations de carte d'identité, si la vérification réussit, il passe à l'étape 03 et si la vérification échoue, il envoie un rappel concernant le renvoi à un premier terminal pour effectuer une nouvelle collecte; et étape 03, le second terminal effectue une vérification de reconnaissance faciale sur un utilisateur, la vérification de reconnaissance faciale étant effectuée au moyen de la collecte d'une image de visage de l'utilisateur et de la comparaison de celle-ci avec une image de portrait sur une carte d'identité pour la vérification, si la vérification réussit, il passe à l'opération suivante et, si la vérification échoue, il rappelle à l'utilisateur d'effectuer une nouvelle reconnaissance faciale. Au moyen du procédé décrit dans la présente invention, la précision de l'authentification d'identité d'utilisateur est améliorée au moyen d'une technologie d'authentification à facteurs multiples.
PCT/CN2018/083075 2017-12-01 2018-04-13 Procédé d'authentification d'identité, dispositif électronique et support d'enregistrement lisible par ordinateur WO2019104930A1 (fr)

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CN201711258376.2 2017-12-01
CN201711258376.2A CN108171032A (zh) 2017-12-01 2017-12-01 一种身份鉴定方法、电子装置及计算机可读存储介质

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