WO2017143571A1 - Procédé, dispositif et terminal d'identification d'empreintes digitales - Google Patents

Procédé, dispositif et terminal d'identification d'empreintes digitales Download PDF

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Publication number
WO2017143571A1
WO2017143571A1 PCT/CN2016/074583 CN2016074583W WO2017143571A1 WO 2017143571 A1 WO2017143571 A1 WO 2017143571A1 CN 2016074583 W CN2016074583 W CN 2016074583W WO 2017143571 A1 WO2017143571 A1 WO 2017143571A1
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WO
WIPO (PCT)
Prior art keywords
fingerprint
living body
person
verified
fingerprint image
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Application number
PCT/CN2016/074583
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English (en)
Chinese (zh)
Inventor
钟志鑫
王信亮
余旖
李顺展
Original Assignee
深圳市汇顶科技股份有限公司
Priority date (The priority date 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 date listed.)
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Application filed by 深圳市汇顶科技股份有限公司 filed Critical 深圳市汇顶科技股份有限公司
Priority to CN201680000663.0A priority Critical patent/CN106104574B/zh
Priority to PCT/CN2016/074583 priority patent/WO2017143571A1/fr
Publication of WO2017143571A1 publication Critical patent/WO2017143571A1/fr

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    • 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
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1347—Preprocessing; Feature extraction
    • 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
    • G06V40/12—Fingerprints or palmprints
    • G06V40/13—Sensors therefor
    • G06V40/1306—Sensors therefor non-optical, e.g. ultrasonic or capacitive sensing
    • 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
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1388—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing

Definitions

  • the present invention relates to the field of information security technologies, and in particular, to a fingerprint identification method, apparatus, and terminal.
  • fingerprints As a unique feature of the human body, fingerprints have lifetime invariance, uniqueness and convenience.
  • fingerprint recognition technology has been widely used in acquisition systems, access control systems, smart phones, smart phones and other devices.
  • fingerprint recognition technology is further applied to application functions such as online fingerprint payment based on fingerprint unlocking of smart phones.
  • the fingerprint recognition technology generally adopts the fingerprint texture feature in the fingerprint image.
  • the illegal user can fake the fake fingerprint according to the acquired fingerprint texture feature, and use the fake fake fingerprint to crack the fingerprint recognition system, thereby causing insufficient security.
  • the present invention aims to solve at least one of the technical problems in the related art to some extent.
  • an object of the present invention is to provide a fingerprint recognition method which can improve the security of fingerprint recognition.
  • Another object of the present invention is to provide a fingerprint recognition apparatus.
  • Another object of the present invention is to provide a terminal.
  • a fingerprint identification method includes: collecting a fingerprint image; extracting features in the fingerprint image; determining, according to the feature, whether the to-be-verified person is a living body; In vivo, fingerprint matching is performed to obtain a fingerprint matching result.
  • the fingerprint identification method provided by the first aspect of the present invention can prevent the illegal user from using the fake fingerprint to crack the fingerprint identification system by performing the living body detection before the fingerprint matching, thereby improving the security of the fingerprint identification.
  • a fingerprint identification device includes: an acquisition module for collecting a fingerprint image; an extraction module for extracting features in the fingerprint image; and a living body recognition module for The feature determines whether the person to be verified is a living body; the fingerprint matching module is configured to perform fingerprint matching when the person to be verified is a living body, and obtain a fingerprint matching result.
  • the fingerprint identification device provided by the embodiment of the second aspect of the present invention can prevent the illegal user from using the fake fingerprint to crack the fingerprint identification system by performing the live detection before the fingerprint matching, thereby improving the security of the fingerprint recognition.
  • a terminal includes a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is disposed inside a space enclosed by the housing, the processor and the memory.
  • a circuit board Provided on a circuit board; a power supply circuit for supplying power to each circuit or device of the terminal; a memory for storing executable program code; the processor running to correspond to the executable program code by reading executable program code stored in the memory a program for performing the following steps: collecting a fingerprint image; extracting features in the fingerprint image; determining, according to the feature, whether the person to be verified is a living body; if the person to be verified is a living body, performing fingerprint matching to obtain a fingerprint matching result .
  • the terminal proposed by the third embodiment of the present invention can prevent the illegal user from using the fake fingerprint to crack the fingerprint identification system by performing the live detection before the fingerprint matching, thereby improving the security of the fingerprint identification.
  • a non-volatile computer storage medium includes: collecting a fingerprint image; extracting features in the fingerprint image; and determining, according to the feature, whether the to-be-verified person is a living body; The person to be verified is a living body, and fingerprint matching is performed to obtain a fingerprint matching result.
  • the non-volatile computer storage medium provided by the embodiment of the fourth aspect of the present invention can prevent the illegal user from using the fake fingerprint to crack the fingerprint identification system by performing the live detection before the fingerprint matching, thereby improving the security of the fingerprint recognition.
  • FIG. 1 is a schematic flow chart of a fingerprint identification method according to an embodiment of the present invention.
  • FIGS. 2a-2b are schematic diagrams showing the arrangement of a fingerprint sensor in an embodiment of the present invention.
  • FIG. 3 is a schematic view showing deformation of a real finger in a pressing process according to an embodiment of the present invention
  • FIG. 4 is a diagram showing relationship between peak-to-peak value and pressure of a fingerprint corresponding to a real fingerprint and a fake fingerprint, respectively, in an embodiment of the present invention
  • FIG. 5 is a schematic flow chart of a living body detection according to an embodiment of the present invention.
  • FIG. 6 is a schematic flow chart of another living body detection in an embodiment of the present invention.
  • Figure 7 is a schematic view showing the characteristics of a sweat hole in an embodiment of the present invention.
  • FIG. 8 is a schematic flow chart of another living body detection in an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of a correlation grayscale image of a real fingerprint and a fake fingerprint in an embodiment of the present invention.
  • FIG. 10 is a schematic diagram showing the relationship between the residual noise mean square error and the statistical number corresponding to the real fingerprint and the fake fingerprint in the embodiment of the present invention.
  • FIG. 11 is a schematic flow chart of another living body detection in an embodiment of the present invention.
  • FIG. 12 is a schematic flowchart diagram of a fingerprint identification method according to another embodiment of the present invention.
  • FIG. 13 is a schematic structural diagram of a fingerprint identification apparatus according to another embodiment of the present invention.
  • FIG. 14 is a schematic structural diagram of a fingerprint identification apparatus according to another embodiment of the present invention.
  • FIG. 15 is a schematic structural diagram of a terminal according to another embodiment of the present invention.
  • FIG. 1 is a schematic flow chart of a fingerprint identification method according to an embodiment of the present invention.
  • the method includes:
  • the person to be verified can put a finger on the sensor for collecting fingerprints of the terminal, so that the sensor can collect the fingerprint image of the person to be verified.
  • a fingerprint sensor may be set in the home screen button 21 of the mobile phone to collect a fingerprint image, or may be set in the preset chip 22 on the back of the mobile phone.
  • a fingerprint sensor that captures a fingerprint image may be set in the home screen button 21 of the mobile phone to collect a fingerprint image, or may be set in the preset chip 22 on the back of the mobile phone.
  • the feature may include one or more of the following:
  • Fingerprint texture features features, sweat hole characteristics, residual noise characteristics, peak-to-peak characteristics.
  • the fingerprint image may be transmitted to the module for feature extraction, and the fingerprint feature is extracted from the fingerprint image by the module for feature extraction.
  • the module for feature extraction is located in the terminal.
  • the method in this embodiment can also be applied to the scenario where the client interacts with the server, and the feature can be extracted by the server. And subsequent verification.
  • the peak-to-peak feature extracted from the fingerprint image can be utilized for live recognition.
  • the real finger will have a slight deformation during the change of the pressing force, and the relative distance between the fingerprint peak 31 and the fingerprint valley 32 will change, that is, the peak-to-peak value of the real fingerprint image will change regularly, and the prosthetic fingerprint Will not exhibit the same regular changes.
  • a plot 41 of the true fingerprint peak-to-peak versus pressure is given, along with a plot 42 of the prosthetic fingerprint peak-to-peak versus pressure. It can be seen from Fig. 4 that the peak-to-peak value of the real fingerprint will change significantly with the increase of the pressure, and the peak-to-peak value of the fingerprint has no obvious change with the increase of the pressure.
  • the living body Based on the peak-to-peak characteristics of the real fingerprint and the prosthetic fingerprint, the living body can be identified as follows.
  • the process of acquiring a fingerprint image, extracting features in the fingerprint image, and detecting the living body includes:
  • S51 acquiring a first fingerprint image and a second fingerprint image, wherein the first fingerprint image is generated by the first verification pressure by the to-be-verified person, and the second fingerprint image is generated by the second verification pressure by the to-be-verified person, the first pressing The pressure is less than the second pressing pressure.
  • the first fingerprint image is a fingerprint image that is collected after the fingerprint controller is lightly pressed by the to-be-verified person
  • the second fingerprint image is a fingerprint image that is collected after the fingerprinting sensor is pressed by the verification object.
  • the terminal may display a prompt message to the person to be verified, for example, prompting the person to be verified to lightly press or repress, thereby collecting the fingerprint image generated by the person to be verified after gently pressing or repressing the fingerprint sensor.
  • S52 Extract a first fingerprint peak-to-peak value in the first fingerprint image, and extract a second fingerprint peak-to-peak value in the second fingerprint image.
  • the first fingerprint peak-to-peak value is the difference between the fingerprint peak and the fingerprint valley in the first fingerprint image
  • the second fingerprint peak-to-peak value is the difference between the fingerprint peak and the fingerprint valley in the second fingerprint image
  • the fingerprint image After the fingerprint image is acquired, it can be extracted and extracted from the peak-to-peak value of the fingerprint.
  • S53 Calculate a difference between the first fingerprint peak-to-peak value and the second fingerprint peak-to-peak value.
  • the difference between the two can be calculated by subtraction.
  • the difference threshold may be preset according to an empirical value or the like. After the difference is obtained, the difference and the difference threshold may be compared to obtain a determination result.
  • whether the person to be verified is a living body can be detected by the peak-to-peak value of the fingerprint according to the light pressure and the heavy pressure.
  • the process of acquiring a fingerprint image, extracting features in the fingerprint image, and detecting the living body includes:
  • S61 Collecting fingerprint images continuously, the continuous fingerprint images are generated by the subject to be verified by pressing pressure of alternating magnitudes.
  • the terminal may display a prompt message to the person to be verified, for example, prompting the person to be verified to lightly press-press-pressure, thereby collecting the pressure to be verified by the person to be verified.
  • a prompt message for example, prompting the person to be verified to lightly press-press-pressure, thereby collecting the pressure to be verified by the person to be verified.
  • S62 extracting a fingerprint peak value and a fingerprint valley value in each fingerprint image, and calculating a peak-to-valley difference between the fingerprint peak value and the fingerprint valley value, that is, a peak-to-peak value, and an inverse change between the statistical peak-to-peak value and the pressing pressure. The number of times.
  • the reverse change means that the larger the pressing pressure is, the smaller the peak value is, or the smaller the pressing pressure is, the larger the peak value is.
  • S63 Determine whether the number of times of the reverse change is greater than a preset number of times threshold, and if yes, execute S64; otherwise, execute S65.
  • the threshold of the number of times may be preset according to an empirical value or the like. After the difference is obtained, the number of times of the reverse change and the threshold of the number of times may be compared to obtain a determination result.
  • whether or not the person to be verified is a living body can be detected by the number of times of the reverse change between the peak-to-peak value and the pressing pressure.
  • the perforation features extracted from the fingerprint image can be utilized for live recognition.
  • Fig. 7 is a schematic view of the sweat hole feature of the fingerprint image
  • an overall schematic 71 of the sweat hole feature and a partially enlarged partial schematic 72 are given.
  • the sweat hole characteristics of the fingerprint can be recorded at the same time.
  • the sweat hole characteristic information of the fingerprint image is basically lost due to limitations of the material to be produced and errors in production. Thereby, living body recognition can be performed according to the characteristics of the sweat hole.
  • the process of acquiring a fingerprint image, extracting features in the fingerprint image, and detecting the living body includes:
  • the person to be verified places a finger on the fingerprint sensor, so that the fingerprint sensor collects the person to be verified. Fingerprint image.
  • the characteristics of the sweat hole include: the number of sweat holes, the relative position information of the sweat hole and the fingerprint pattern, and the like.
  • the sweat hole feature can be obtained and recorded when the user registers.
  • the judgment result is consistent when the extracted sweat hole features are set to match any of the previously selected sweat hole features according to actual scenes.
  • the storage user identifier and the sweat hole feature may be associated with the storage, and the login is performed before the verification is performed.
  • the user corresponding to the to-be verified may be obtained from the pre-stored information according to the user identifier of the to-be-verified person.
  • the residual noise features extracted from the fingerprint image may be utilized for live recognition.
  • FIG 9 is a schematic diagram of a correlated grayscale image of a real fingerprint and a fake fingerprint.
  • They are the grayscale 911 of the real fingerprint, the grayscale 912 after the real fingerprint denoising, the residual noise grayscale 913 of the real fingerprint, the grayscale 921 of the 2D fake fingerprint, the grayscale 922 of the 2D false fingerprint, and the 2D fake fingerprint.
  • the process of acquiring a fingerprint image, extracting features in the fingerprint image, and detecting the living body includes:
  • S111 Acquire a fingerprint image.
  • the person to be verified places a finger on the fingerprint sensor, so that the fingerprint image of the person to be verified is collected by the fingerprint sensor.
  • the fingerprint image may be subjected to median filtering to obtain a filtered fingerprint image, and then the difference between the filtered fingerprint image and the filtered fingerprint image may be calculated to obtain residual noise. Sign.
  • the mean square error threshold may be preset according to an empirical value or the like. After obtaining the mean square error of the residual noise, the mean square error of the residual noise and the preset mean square error threshold may be compared to obtain a determination result.
  • whether the person to be verified is a living body can be detected according to the residual noise characteristic.
  • the fingerprint texture feature can be extracted from the fingerprint image, and in addition, the fingerprint texture feature can be acquired and recorded when the user registers.
  • Fingerprint matching is to compare the currently extracted fingerprint texture features with pre-recorded fingerprint texture features. When the two are consistent (same or within the same error range), the fingerprint matching result is fingerprint matching, otherwise the fingerprint does not match. .
  • fingerprint matching is used for matching in fingerprint matching, and other features may be used for matching.
  • fingerprint matching can also be performed using features employed in living body detection.
  • the corresponding operation may be performed according to the fingerprint matching result.
  • the fingerprint matching result is a fingerprint matching
  • the person to be verified may be allowed to perform a corresponding operation, for example, a fingerprint unlocking terminal, a fingerprint payment, a fingerprint input, a fingerprint login, and the like. If the fingerprint matching result does not match, the corresponding operation can be rejected.
  • the fingerprint identification process can be ended, and subsequent fingerprint matching is not performed, and information such as verification failure is directly fed back.
  • the living body detection and the fingerprint matching can also be performed in parallel, that is, the fingerprint texture feature, the peak-to-peak feature, the sweat hole feature or the residual noise feature are extracted in the fingerprint image at the same time, and the living body judgment and the fingerprint matching are simultaneously performed.
  • the corresponding person is allowed to perform the corresponding operation; when it is determined that the person to be verified is a prosthesis or the fingerprint matching fails, the information such as the verification failure is fed back. Therefore, while the living body detection is increased, the time of the original fingerprint matching is not increased.
  • the illegal user can be prevented from using the fake fingerprint to crack the fingerprint identification system, thereby improving the security of the fingerprint identification.
  • the fraudulent method of the real living fake fingerprint can be avoided, and the safety is further improved.
  • live detection directly from the fingerprint image it is possible to avoid additional hardware costs and improve compatibility. Further, by the above-described different methods of living body detection, diversification and flexibility of the living body detection method can be achieved.
  • FIG. 12 is a schematic flow chart of a fingerprint identification method according to another embodiment of the present invention.
  • the method includes:
  • S121 Determine the security level used by the current application.
  • the security level can be divided into I, II, and III, and is sequentially increased in the order of I, II, and III.
  • Level I security requirements it is not necessary to perform live detection, and fingerprint matching is performed only according to fingerprint texture features.
  • Level II security the process of living body detection is added on the basis of the level I safety, and the living body detection is performed according to the characteristics of the sweat hole and/or the residual noise characteristics.
  • Level III security requirements the user is required to press different strengths to extract the peak-to-peak characteristics of the fingerprint, and then perform the living body detection according to the peak-to-peak characteristics.
  • the III-level safety requirement only the peak may be used for the living body detection.
  • the peak feature or it may be based on a level II security level, ie, based on peak-to-peak characteristics during live detection, and also based on sweat feature and/or residual noise characteristics.
  • S122 Determine whether the living body detection is required according to the currently used security level. If yes, execute S123; otherwise, execute S126.
  • the security level is level II or level III, in vivo detection is required, and if it is level I, in vivo detection is not required.
  • S123 Acquire a fingerprint image according to the currently used security level.
  • the normal fingerprint collection method may be adopted, and the fingerprint image is collected after the fingerprint is placed on the fingerprint sensor by the person to be verified.
  • a prompt message may be displayed to the person to be verified, for example, prompting the person to be verified to lightly press or press, or lightly pressing-heavy-light The pressure is alternately pressed to collect a fingerprint image generated by the person to be verified using different pressing pressures.
  • the security level is level II
  • the sweat hole feature or residual noise characteristics can be extracted.
  • the peak-to-peak feature can be extracted.
  • S125 Determine whether it is a living body according to the extracted feature, if yes, execute S126, otherwise, execute S127.
  • the fingerprint texture features are extracted from the fingerprint image and compared with the pre-stored fingerprint texture features. If they are identical or within the error range, the fingerprint matching result is a fingerprint matching, otherwise the fingerprint matching result is not matched. Then, the corresponding operation can be performed according to the fingerprint matching result. For example, when the fingerprint is matched, the person to be verified is allowed to perform subsequent operations, for example, fingerprint unlocking, fingerprint payment, fingerprint entry, fingerprint login, and the like. If the fingerprints do not match, the person to be verified may be refused to perform subsequent operations, and the fingerprint unmatched information is fed back to the person to be verified.
  • subsequent operations for example, fingerprint unlocking, fingerprint payment, fingerprint entry, fingerprint login, and the like. If the fingerprints do not match, the person to be verified may be refused to perform subsequent operations, and the fingerprint unmatched information is fed back to the person to be verified.
  • the prosthesis information can be fed back to the person to be verified. After that, the verification process can be ended, and the person to be verified is not allowed to perform subsequent fingerprint unlocking operations.
  • the illegal user can be prevented from using the fake fingerprint to crack the fingerprint identification system, thereby improving the security of the fingerprint identification.
  • the fraudulent method of the real living fake fingerprint can be avoided, and the security is further improved.
  • live detection directly from the fingerprint image it is possible to avoid additional hardware costs and improve compatibility.
  • diversification and flexibility of the living body detection method can be achieved.
  • the actual requirements can be better met.
  • FIG. 13 is a schematic structural diagram of a fingerprint identification apparatus according to another embodiment of the present invention.
  • the apparatus 130 includes an acquisition module 131, an extraction module 132, a living body identification module 133, and a fingerprint matching module 134.
  • the collecting module 131 is configured to collect a fingerprint image
  • An extracting module 132 configured to extract features in the fingerprint image
  • the living body identification module 133 is configured to determine, according to the feature, whether the person to be verified is a living body
  • the fingerprint matching module 134 is configured to perform fingerprint matching when the person to be verified is a living body, and obtain a fingerprint matching result.
  • the fingerprint image includes: a first fingerprint image generated by the first verification pressure and a second fingerprint image generated by the second verification pressure generated by the to-be-verified person.
  • the first pressing pressure is less than the second pressing pressure;
  • the extracted features include: a first fingerprint peak-to-peak value extracted from the first fingerprint image, and a second fingerprint peak-to-peak value extracted from the second fingerprint image;
  • the living body identification module 133 is specifically configured to:
  • the difference is greater than the preset difference threshold, it is determined that the person to be verified is a living body.
  • the fingerprint image includes: a fingerprint image generated by the to-be-verified person using alternating pressing pressures;
  • the extracted features include: a peak-to-peak value of the fingerprint extracted in each fingerprint image;
  • the living body identification module 133 is specifically configured to:
  • the number of reverse changes is greater than a preset number of times threshold, it is determined that the person to be verified is a living body.
  • the extracted features are: sweat hole characteristics
  • the living body identification module 133 is specifically configured to:
  • the extracted features are: residual noise characteristics;
  • the living body identification module 133 is specifically configured to:
  • the mean square error is less than the preset mean square error threshold, it is determined that the person to be verified is a living body.
  • the apparatus further includes:
  • a determination module 135 is configured to determine a security level used by the current application.
  • the extraction module 132 is specifically configured to:
  • the device in this embodiment corresponds to the foregoing method embodiment. Therefore, the specific content of each module of the device in this embodiment can be referred to the related description in the method embodiment, and is not described in detail herein.
  • the illegal user can be prevented from using the fake fingerprint to crack the fingerprint identification system, thereby improving the security of the fingerprint identification.
  • the fraudulent method of the real living fake fingerprint can be avoided, and the security is further improved.
  • live detection directly from the fingerprint image it is possible to avoid additional hardware costs and improve compatibility. Further, by the above-described different methods of living body detection, diversification and flexibility of the living body detection method can be achieved.
  • FIG. 15 is a schematic structural diagram of a terminal according to another embodiment of the present invention.
  • the terminal 150 includes: a casing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is disposed inside the space enclosed by the casing, the processor and the memory are disposed on the circuit board; and the power circuit is used
  • the power is supplied to each circuit or device of the terminal;
  • the memory is used to store executable program code;
  • the processor runs the program corresponding to the executable program code by reading the executable program code stored in the memory for performing the following steps:
  • fingerprint matching is performed to obtain a fingerprint matching result.
  • another embodiment of the present invention also provides a non-volatile computer storage medium storing one or more modules for performing the following steps:
  • fingerprint matching is performed to obtain a fingerprint matching result.
  • the illegal user can be prevented from using the fake fingerprint to crack the fingerprint identification system, thereby improving the security of the fingerprint identification.
  • the fraudulent method of the real living fake fingerprint can be avoided, and the security is further improved.
  • live detection directly from the fingerprint image it is possible to avoid additional hardware costs and improve compatibility. Further, by the above-described different methods of living body detection, diversification and flexibility of the living body detection method can be achieved.
  • portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
  • multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.
  • each functional unit in each embodiment of the present invention may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated modules, if implemented in the form of software functional modules and sold or used as stand-alone products, may also be stored in a computer readable storage medium.
  • the above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

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  • Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
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  • Computer Vision & Pattern Recognition (AREA)
  • Collating Specific Patterns (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

La présente invention concerne un procédé, un dispositif et un terminal d'identification d'empreintes digitales. Le procédé d'identification d'empreintes digitales consiste : à collecter une image d'empreintes digitales (S11) ; à extraire une caractéristique de l'image d'empreintes digitales (S12) ; à déterminer, sur la base de la caractéristique, si un candidat qui doit être testé, est une entité vivante (S13) ; et si le candidat qui doit être testé, est une entité vivante, à mette alors en correspondance les empreintes digitales et à acquérir un résultat de mise en correspondance d'empreintes digitales (S14). Ce procédé peut aider à améliorer la sécurité d'un processus d'identification d'empreintes digitales.
PCT/CN2016/074583 2016-02-25 2016-02-25 Procédé, dispositif et terminal d'identification d'empreintes digitales WO2017143571A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680000663.0A CN106104574B (zh) 2016-02-25 2016-02-25 指纹识别方法、装置和终端
PCT/CN2016/074583 WO2017143571A1 (fr) 2016-02-25 2016-02-25 Procédé, dispositif et terminal d'identification d'empreintes digitales

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CN112241655A (zh) * 2019-07-16 2021-01-19 北京小米移动软件有限公司 指纹图像处理方法和装置
US11163970B1 (en) 2020-06-16 2021-11-02 Google Llc Optical fingerprint system with varying integration times across pixels
CN116935519A (zh) * 2023-09-15 2023-10-24 四川金投科技股份有限公司 一种基于近距离无线通信技术的智能锁及其控制方法

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CN106682473A (zh) * 2016-12-20 2017-05-17 深圳芯启航科技有限公司 一种用户身份信息的识别方法及其装置
US11144772B2 (en) 2017-01-12 2021-10-12 Zkteco Co., Ltd. Method and system for fingerprint security
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CN107239745B (zh) * 2017-05-15 2021-06-25 努比亚技术有限公司 指纹模拟方法及对应的移动终端
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