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WO2018137286A1 - Procédé de verification d'empreinte digitale et dispositif électronique - Google Patents

Procédé de verification d'empreinte digitale et dispositif électronique Download PDF

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Publication number
WO2018137286A1
WO2018137286A1 PCT/CN2017/078490 CN2017078490W WO2018137286A1 WO 2018137286 A1 WO2018137286 A1 WO 2018137286A1 CN 2017078490 W CN2017078490 W CN 2017078490W WO 2018137286 A1 WO2018137286 A1 WO 2018137286A1
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WO
WIPO (PCT)
Prior art keywords
verification
fingerprint
scores
module
comparison
Prior art date
Application number
PCT/CN2017/078490
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English (en)
Chinese (zh)
Inventor
张永清
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创智能科技股份有限公司
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Application filed by 创智能科技股份有限公司 filed Critical 创智能科技股份有限公司
Publication of WO2018137286A1 publication Critical patent/WO2018137286A1/fr

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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

Definitions

  • the invention relates to a verification method, in particular to a fingerprint verification method and an electronic device.
  • biometrics include faces, sounds, irises, retinas, veins, fingerprints, and palmprint recognition. Since each person's fingerprints are unique and fingerprints are not easily changed with age or physical health, fingerprint recognition technology has been widely used in various fields.
  • the Fault Acceptance Rate (FAR) and the Fault Rejection Rate (FRR) are often used as evaluation indicators of the fingerprint identification system in the technical field of fingerprint recognition.
  • the error acceptance rate is a probability that a user who is illegal is mistakenly judged to be a legitimate user, and the lower the error acceptance rate, the higher the security of the fingerprint recognition device.
  • the false rejection rate is a probability that a legitimate user is mistakenly judged to be an illegal user, and the lower the false rejection rate, the easier it is to use.
  • the fingerprint recognition device acquires a fingerprint image by one press of the user for comparison.
  • the present invention is directed to a verification method, and more particularly to a fingerprint verification method and an electronic device to which the fingerprint verification method is applied.
  • the fingerprint verification method of the present invention includes: obtaining a plurality of fingerprint images; comparing each of the plurality of fingerprint images with a preset fingerprint image to obtain a plurality of first comparison results; Each two fingerprint images in the fingerprint image are compared with each other to obtain at least one a second comparison result; and determining whether the plurality of fingerprint images pass the verification according to the plurality of first alignment results and the at least one second comparison result.
  • the method further includes generating a plurality of initial scores according to the plurality of first comparison results. Determining, according to the plurality of first comparison results and the at least one second comparison result, whether the plurality of fingerprint images pass the verification comprises: adjusting the plurality of initials according to the at least one second comparison result a score to obtain a plurality of verification scores; and determining whether the plurality of fingerprint images pass the verification based on the plurality of verification scores.
  • the step of determining whether the plurality of fingerprint images pass the verification according to the plurality of verification scores comprises determining whether the plurality of verification scores includes at least one first that meets a verification threshold value. Verify the score. If it is determined that the plurality of verification scores include the at least one first verification score, determining that the first fingerprint image of the plurality of fingerprint images corresponding to the at least one first verification score passes verification.
  • the method further includes generating, according to the plurality of first comparison results, at least one reference alignment result, and according to the at least one reference comparison result and the at least one second ratio Obtain at least one similarity parameter for the result.
  • Adjusting the plurality of initial scores according to the at least one second alignment result to obtain the plurality of verification scores includes adjusting the plurality of initial scores according to the at least one similarity parameter to obtain the plurality of verifications fraction.
  • the step of adjusting the plurality of initial scores according to the at least one similarity parameter to obtain the plurality of verification scores comprises determining whether the at least one similarity parameter is less than similarity Threshold value. If it is determined that the at least one similarity parameter is not less than the similarity threshold, the plurality of initial scores are adjusted according to the first rule to obtain the plurality of verification scores. If it is determined that the at least one similarity parameter is less than the similarity threshold, the plurality of initial scores are adjusted according to a second rule to obtain the plurality of verification scores.
  • the electronic device of the present invention includes: an image acquisition module, configured to obtain a plurality of fingerprint images; and a comparison module, configured to compare each of the plurality of fingerprint images with a preset fingerprint image to obtain a plurality of First aligning the results, and comparing each of the plurality of fingerprint images to each other to obtain at least one second comparison result; and a verification module for determining results according to the plurality of first alignments Determining the plurality of results with the at least one second alignment result Whether the fingerprint image has passed verification.
  • the comparison module is further configured to generate a plurality of initial scores according to the plurality of first alignment results.
  • the verification module is configured to adjust the plurality of initial scores according to the at least one second comparison result to obtain a plurality of verification scores, and determine whether the plurality of fingerprint images pass the verification according to the plurality of verification scores.
  • the verification module is configured to determine whether the plurality of verification scores includes at least one first verification score that meets a verification threshold. If it is determined that the plurality of verification scores include the at least one first verification score, the verification module is configured to determine that the first fingerprint image in the plurality of fingerprint images corresponding to the at least one first verification score passes verification .
  • the comparison module is configured to generate at least one reference comparison result according to the plurality of first comparison results, and according to the at least one reference comparison result and the at least A second alignment result obtains at least one similarity parameter.
  • the verification module adjusts the plurality of initial scores according to the at least one similarity parameter to obtain the plurality of verification scores.
  • the verification module is configured to determine whether the at least one similarity parameter is less than a similarity threshold. If it is determined that the at least one similarity parameter is not less than the similarity threshold, the verification module is configured to adjust the plurality of initial scores according to the first rule to obtain the plurality of verification scores. If it is determined that the at least one similarity parameter is smaller than the similarity threshold, the verification module is configured to adjust the multiple initial scores according to the second rule to obtain the multiple verification scores.
  • the fingerprint verification method and the electronic device of the present invention can perform fingerprint verification by acquiring a plurality of fingerprint images and comparing the obtained plurality of fingerprint images one by one with a preset fingerprint image.
  • FIG. 1 is a block diagram of an electronic device according to an embodiment of the invention.
  • FIG. 2 is a flow chart showing a fingerprint verification method according to an embodiment of the invention.
  • FIG. 3 is a schematic diagram of a captured fingerprint image and a preset fingerprint image according to an embodiment of the invention
  • FIG. 4 is a schematic diagram of a fingerprint verification method according to an embodiment of the invention.
  • FIG. 5 is a schematic diagram of a fingerprint verification method according to another embodiment of the present invention.
  • CA(1) ⁇ CA(5) the first comparison result
  • the invention determines whether the fingerprint to be verified passes the verification by obtaining a plurality of fingerprint images of the fingerprint to be verified. And each of the obtained fingerprint images is respectively separated from the preset fingerprint image. Performing fingerprint verification together with a plurality of comparison results between each other and the acquired multiple comparison results of each of the two fingerprint images with each other can improve the accuracy of fingerprint verification.
  • FIG. 1 is a block diagram of an electronic device shown in accordance with an embodiment of the present invention.
  • the electronic device 10 of the present embodiment is, for example, a smart phone, a tablet computer, a desktop computer or a notebook computer or other similar electronic device having a fingerprint sensor.
  • the electronic device 10 includes a fingerprint sensor 110, a processor 120, and a storage device 130.
  • the fingerprint sensor 110 can be an optical, resistive, capacitive or other type of sensing element for sensing a user's operation (eg, touching or accessing) to obtain a fingerprint image.
  • a user's operation eg, touching or accessing
  • the invention is not limited thereto.
  • a person skilled in the art can select a fingerprint sensor 110 that acquires a fingerprint image in a different manner as needed.
  • the storage device 130 can be any type of fixed or removable random access memory (RAM), read-only memory (ROM), flash memory (flash memory) or Similar elements or combinations of the above elements.
  • the storage device 130 is used to record the image acquisition module 131, the comparison module 132, and the verification module 133. These modules are, for example, programs stored in the storage device 130.
  • storage device 130 may be used to store fingerprint images acquired by fingerprint sensor 110.
  • the processor 120 is, for example, a central processing unit (CPU) or other programmable general purpose or special purpose microprocessor (Microprocessor), digital signal processor (DSP), programmable controller. , Application Specific Integrated Circuits (ASICs), Programmable Logic Devices (PLDs), or other similar devices or a combination of these devices.
  • CPU central processing unit
  • Microprocessor programmable general purpose or special purpose microprocessor
  • DSP digital signal processor
  • ASICs Application Specific Integrated Circuits
  • PLDs Programmable Logic Devices
  • the processor 120 is coupled to the fingerprint sensor 110 and the storage device 130, and loads the image acquisition module 131, the comparison module 132, and the verification module 133 from the storage device 130 to perform the fingerprint verification method of the present invention.
  • the following is an example to illustrate this method.
  • FIG. 2 is a flow chart of a fingerprint verification method according to an embodiment of the invention.
  • the method of the present embodiment is applied to the electronic device 10 shown in FIG. 1, and the detailed steps of the fingerprint verification method of the present invention are described below with the components in the electronic device 10.
  • the processor 120 executes the image acquisition module 131 to obtain a plurality of fingerprint images through the fingerprint sensor 110.
  • the electronic device 10 shown in FIG. 1 may further include A display device (not shown).
  • the electronic device 10 can display prompt information on the number of presses of the user input fingerprint on the display device, and the fingerprint sensor 110 acquires a plurality of fingerprint images with each pressing action of the user.
  • the processor 120 may execute the image acquisition module 131 and may perform an image processing operation on the image acquired by the fingerprint sensor 110 to obtain a fingerprint image to be used for comparison.
  • the image processing operations described above may include performing grayscale processing on the fingerprint image, or analyzing features of the fingerprint image to calculate a geometric relation or the like of the corresponding fingerprint image.
  • the above geometric relationship is, for example, characteristic information about the relative position of the fingerprint feature, the relative direction, or the distance between the features.
  • the processor 120 executes the comparison module 132 to compare the plurality of fingerprint images with the preset fingerprint image to obtain a plurality of first comparison results.
  • the comparison module 132 can employ different alignment algorithms to perform the alignment operation of the fingerprint images in response to different application requirements. For example, the comparison module 132 can generate a first alignment result by comparing the geometric relationship of each fingerprint image to the geometric relationship of the preset fingerprint image. Therefore, the first alignment result corresponding to one fingerprint image may include features (or feature information) to indicate the same or similar between the fingerprint image and the preset fingerprint image.
  • the processor 120 also executes the comparison module 132 to calculate an initial score corresponding to each fingerprint image according to the first comparison result. The comparison module 132 can calculate an initial score based on the first alignment result based on the alignment algorithm employed.
  • the preset fingerprint image may be a fingerprint image that is pre-established according to the fingerprint of the user.
  • the storage device 130 of FIG. 1 is also used to record a fingerprint registration module (not shown).
  • the processor 120 can execute a fingerprint registration module and can take one or more fingerprint images through the fingerprint sensor 110 to generate a registered fingerprint image.
  • the processor 120 may execute a fingerprint processing module to perform an image processing operation on the fingerprint image acquired by the fingerprint sensor 110, and generate a registered fingerprint image according to the image processed fingerprint image.
  • the processor 120 may execute a fingerprint registration module to combine the acquired plurality of fingerprint images into one registered fingerprint image, and store the registered fingerprint image into the storage device 130.
  • the fingerprint registration module may also separately store the acquired plurality of fingerprint images into the storage device 130.
  • the preset fingerprint image may also be stored in a storage device external to the electronic device 10, and the electronic device 10 may obtain a preset fingerprint image through the network.
  • step S205 the processor 120 performs the comparison module 132 to Each of the two fingerprint images in the fingerprint image is compared with each other to obtain at least one second alignment result.
  • the alignment module 132 can generate a second alignment result by comparing the geometric relationship of one fingerprint image to another.
  • the second alignment result corresponding to each of the two fingerprint images may include features (or feature information) to indicate the same or similar between the two fingerprint images.
  • the first alignment result and the second alignment result can be used to indicate the degree of similarity between the two fingerprint images.
  • the comparison module 132 may generate a second comparison result.
  • the comparison module 132 may generate two or more second comparison results.
  • step S207 the processor 120 executes the verification module 133 to determine whether the plurality of fingerprint images pass the verification according to the plurality of first comparison results and the at least one second comparison result.
  • the processor 120 executes the verification module 133 to adjust the initial score calculated according to the first comparison result according to the second comparison result to generate a verification score corresponding to each fingerprint image. For example, in a case, the verification module 133 determines that the degree of similarity between two fingerprint images is high according to a certain second comparison result, and the verification module 133 respectively increases the initial scores of the two fingerprint images. To generate a verification score. In other words, the verification score in this case will be greater than the initial score.
  • the verification module 133 determines that the degree of similarity between the two fingerprint images is not high enough according to a certain second comparison result, and the verification module 133 respectively lowers the initial scores of the two fingerprint images. To generate a verification score. In other words, the verification score in this other case will be smaller than the initial score.
  • step S207 after obtaining the verification score, the processor 120 executes the verification module 133 to determine whether the verification score is higher than the verification threshold to determine whether the fingerprint image passes the verification. For example, the verification module 133 determines whether a plurality of verification scores include a verification score (also referred to as a first verification score) that meets the verification threshold. If it is determined that the plurality of verification scores include the first verification score that meets the verification threshold, the verification module 133 determines that the fingerprint image (also referred to as the first fingerprint image) corresponding to the first verification score passes the verification. However, in another embodiment, the processor 120 executes the verification module 133 to determine whether the initial score is above the verification threshold to determine whether the initial score is to be adjusted based on the second alignment result.
  • a verification score also referred to as a first verification score
  • the verification module 133 determines that the initial score of a certain fingerprint image is higher than the verification threshold, and thus directly determines that the fingerprint image passes verification. In another case, the verification module 133 determines that the initial score of a certain fingerprint image is lower than the verification threshold, and thus according to the second comparison result corresponding to the fingerprint image. Adjust the initial score to generate a new verification score. Then, based on the generated verification score, it is determined whether the fingerprint image passes the verification.
  • the processor 120 may perform the comparison module 132 to generate at least one reference alignment result according to the first comparison result described above. For example, the comparison module 132 obtains the reference alignment result by comparing each of the two first alignment results. Next, the comparison module 132 can generate a similarity parameter according to the obtained reference alignment result and the second comparison result described above. Then, the processor 120 may execute the verification module 133 to adjust the initial score according to the acquired similarity parameter to generate a verification score, and then determine whether the plurality of fingerprint images pass the verification according to the verification score.
  • FIG. 3 is a schematic diagram of a captured fingerprint image and a preset fingerprint image according to an embodiment of the invention.
  • the electronic device 10 executes the image acquisition module 131 and detects multiple presses of the user by the fingerprint sensor 110 to acquire a plurality of fingerprint images 321 , 322 , 323 corresponding to the user fingerprint 30 .
  • a preset fingerprint image 311 corresponding to the user fingerprint 30 has been stored in the storage device 130 of the electronic device 10.
  • the acquired fingerprint images 321, 322, 323 and the preset fingerprint image 311 respectively have overlapping regions.
  • the same or similar features (or feature information) between the two fingerprint images may be included in the overlapping area between the two fingerprint images.
  • the processor 120 executes the comparison module 132 to find the overlapping area according to the geometric relationship of each fingerprint image.
  • the comparison module 132 generates a first comparison result corresponding to each of the fingerprint images 321, 322, 323 according to the overlapping area, and can calculate a corresponding initial according to the first comparison result of each of the fingerprint images 321, 322, 323. fraction. Further, the acquired fingerprint images 321, 322, and 323 also have overlapping regions with each other. The processor 120 executes the comparison module 132 to generate a second alignment result between each of the two fingerprint images 321 , 322 , 323 according to the overlap region.
  • FIG. 4 is a schematic diagram of a fingerprint verification method according to an embodiment of the invention.
  • the processor 120 executes the image acquisition module 131 and acquires two fingerprint images through the fingerprint sensor 110 to perform a fingerprint verification operation.
  • the processor 120 executes the image acquisition module 131 to obtain fingerprint images 421 and 422.
  • the processor 120 performs a comparison module 132 to compare the fingerprint image 421 with the preset fingerprint image 411 to generate a comparison result CA(1), and the fingerprint image 422 and the preset fingerprint.
  • the image 411 is aligned to produce a comparison result CA(2).
  • the comparison module 132 also compares the fingerprint image 421 with the fingerprint image 422 to produce a comparison result CB(1).
  • the comparison module 132 further calculates an initial score of the corresponding fingerprint image 421 according to the comparison result CA(1), and calculates an initial score of the corresponding fingerprint image 422 according to the comparison result CA(2).
  • the processor 120 executes the verification module 133 to determine whether the fingerprint image 421 and the fingerprint image 422 pass the verification based on the comparison result CA(1) and the comparison result CA(2).
  • the processor 120 may first perform the comparison module 132 to generate a reference comparison result CR(1) between the fingerprint image 421 and the fingerprint image 422 according to the comparison result CA(1) and the comparison result CA(2). . Further, the comparison module 132 obtains a similarity parameter based on the reference comparison result CR(1) and the comparison result CB(1) between the fingerprint image 421 and the fingerprint image 422. For example, the processor 120 performs the comparison module 132 to compare the geometric relationship between the corresponding fingerprint image 421 and the corresponding preset fingerprint image 411 to obtain an alignment between the fingerprint image 421 and the preset fingerprint image 411. Results CA (1).
  • the comparison result CA(1) includes similarity information indicating the same or similar feature (or feature information) between the fingerprint image 421 and the preset fingerprint image 411.
  • the comparison module 132 compares the geometric relationship between the corresponding fingerprint image 422 and the corresponding preset fingerprint image 411 to obtain the comparison result CA(2) between the fingerprint image 422 and the preset fingerprint image 411.
  • the comparison result CA(2) includes similarity information to indicate the same or similar feature (or feature information) between the fingerprint image 422 and the preset fingerprint image 411.
  • the comparison module 132 compares the reference similarity information between the fingerprint image 421 and the fingerprint image 422 as a reference comparison result CR according to the similarity information of the comparison result CA(1) and the comparison result CA(2). (1).
  • the reference similarity information between the fingerprint image 421 and the fingerprint image 422 may be part of the similarity information between the fingerprint image 421 and the fingerprint image 422.
  • the comparison module 132 can analyze the same feature information between the two similarity information to obtain the reference similarity information. Further, the comparison module 132 determines the degree of similarity between the reference comparison result CR(1) between the fingerprint image 421 and the fingerprint image 422 and the comparison result CB(1) to obtain a similarity parameter. For example, the comparison module 132 may calculate the repetition rate of the similarity information of the reference comparison result CR(1) and the similarity information of the comparison result CB(1) as the similarity parameter.
  • the processor 120 may execute the verification module 133 to adjust the initial score of the corresponding fingerprint image 421 according to the similarity parameter to generate a verification score corresponding to the fingerprint image 421, and adjust the corresponding fingerprint image 422 according to the similarity parameter.
  • the initial score is to generate a verification score for the corresponding fingerprint image 422.
  • the verification module 133 determines how to adjust the initial score by determining whether the similarity parameter is less than a preset similarity threshold. example For example, if it is determined that the similarity parameter is not less than (ie, equal to or greater than) the similarity threshold, the verification module 133 adjusts the initial score according to the first rule to generate a verification score.
  • the verification module 133 adjusts the initial score according to the second rule to generate a verification score.
  • the verification score generated according to the first rule may be greater than or equal to the initial score, and the verification score generated according to the second rule may be smaller than the initial score.
  • the verification module 133 can determine whether the fingerprint images 421 and 422 pass the verification by determining whether the verification score meets the preset verification threshold.
  • the compliance threshold value refers to a value greater than or equal to the verification threshold. For example, when it is determined that the verification score of the corresponding fingerprint image 421 (or the fingerprint image 422) is greater than or equal to the verification threshold, the verification module 133 determines that the fingerprint image 421 (or the fingerprint image 422) passes the verification. When it is determined that the verification score of the corresponding fingerprint image 421 (or the fingerprint image 422) is less than the verification threshold, the verification module 133 determines that the fingerprint image 421 (or the fingerprint image 422) has not passed the verification.
  • the verification module 133 may determine that the current fingerprint verification result is the verification when one of the fingerprint image 421 and the fingerprint image 422 meets the verification threshold. However, in other embodiments, the verification module 133 may also determine that the current fingerprint verification result is pass verification when both the fingerprint image 421 and the fingerprint image 422 meet the verification threshold.
  • FIG. 5 is a schematic diagram of a fingerprint verification method according to another embodiment of the present invention.
  • the processor 120 executes the image acquisition module 131 and acquires three fingerprint images through the fingerprint sensor 110 to perform a fingerprint verification operation.
  • the processor 120 executes the image acquisition module 131 to obtain fingerprint images 521, 522, 523.
  • the processor 120 executes the comparison module 132 to compare the fingerprint images 521, 522, and 523 with the preset fingerprint image 511, respectively, and generates comparison results CA(3), CA(4), CA(5).
  • the comparison module 132 also compares the fingerprint image 521 with the fingerprint image 522 to generate a comparison result CB(2), compares the fingerprint image 522 with the fingerprint image 523 to generate a comparison result CB(3), and prints the fingerprint.
  • the image 521 is compared with the fingerprint image 523 to produce a comparison result CB(4).
  • the comparison module 132 also calculates initial scores of the corresponding fingerprint images 521, 522, and 523 based on the comparison results CA(3), CA(4), and CA(5), respectively.
  • the comparison module 132 further generates a reference comparison result CR(2) between the fingerprint image 521 and the fingerprint image 522 according to the comparison result CA(3) and the comparison result CA(4), according to the comparison result CA ( 4) and the comparison result CA(5) to generate a reference between the fingerprint image 522 and the fingerprint image 523
  • the result CR(3) is compared, and a reference comparison result CR(4) between the fingerprint image 521 and the fingerprint image 523 is generated based on the comparison result CA(3) and the comparison result CA(5).
  • the comparison module 132 can obtain a similarity parameter according to the reference comparison result CR(2) and the comparison result CB(2), and obtain the similarity parameter according to the reference comparison result CR(3) and the comparison result CB(3). Another similarity parameter, and another similarity parameter is obtained based on the reference alignment result CR(4) and the alignment result CB(4).
  • the fingerprint images 521, 522, 523 are associated with two similarity parameters, respectively.
  • the processor 120 may execute the verification module 133 to find the maximum similarity parameter among the similarity parameters associated with each fingerprint image, and then adjust the initial score of each fingerprint image according to the maximum similarity parameter.
  • the fingerprint image 521 is associated with the similarity parameter obtained by the reference comparison result CR(2) and the comparison result CB(2), and is also associated with the reference comparison result CR(4) and the comparison result CB ( 4) The similarity parameters obtained.
  • the hypothesis verification module 133 determines that the similarity parameter obtained by the reference comparison result CR(2) and the comparison result CB(2) is greater than that obtained by the reference comparison result CR(4) and the comparison result CB(4).
  • the verification module 133 will adjust the initial score of the fingerprint image 521 based on the similarity parameter obtained by the reference comparison result CR(2) and the comparison result CB(2) to generate a verification score. Further, the verification module 133 can determine the result of the fingerprint verification based on the verification score by a method similar to the embodiment shown in FIG.
  • the fingerprint verification method of the present invention when the fingerprint verification method of the present invention performs a fingerprint verification operation, a plurality of fingerprint images of the user are obtained to perform comparison to determine whether the verification result is a pass verification. Moreover, the score value between the obtained fingerprint image and the preset fingerprint image for indicating the comparison result may be adjusted according to the degree of similarity between each two fingerprint images. In this way, the reliability of the comparison result can be improved, thereby improving the accuracy of fingerprint verification.

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  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

La présente invention concerne un procédé de vérification d'empreinte digitale et un dispositif électronique. Le procédé de vérification d'empreinte digitale consiste à : obtenir une pluralité d'images d'empreinte digitale; comparer chaque image de la pluralité d'images d'empreinte digitale à une image d'empreinte digitale prédéfinie pour obtenir une pluralité de premiers résultats de comparaison; comparer chaque image de la pluralité d'images d'empreintes digitales l'une à l'autre pour obtenir au moins un second résultat de comparaison; et déterminer si les multiples images d'empreintes digitales passent la vérification selon la pluralité de premiers résultats de comparaison et l'ou les seconds résultats de comparaison. Le procédé de vérification d'empreinte digitale et le dispositif électronique de la présente invention peuvent améliorer la précision de la vérification d'empreinte digitale.
PCT/CN2017/078490 2017-01-24 2017-03-29 Procédé de verification d'empreinte digitale et dispositif électronique WO2018137286A1 (fr)

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WO2020073166A1 (fr) * 2018-10-08 2020-04-16 深圳市汇顶科技股份有限公司 Procédé et appareil de reconnaissance d'empreintes digitales et dispositif terminal

Citations (3)

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Publication number Priority date Publication date Assignee Title
CN1353844A (zh) * 1999-05-11 2002-06-12 奥森泰克公司 用来创建合成指纹图象的方法和设备
CN1588425A (zh) * 2004-07-15 2005-03-02 清华大学 多注册指纹融合方法
CN102708360A (zh) * 2012-05-09 2012-10-03 深圳市亚略特生物识别科技有限公司 一种指纹模板生成及自动更新的方法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1353844A (zh) * 1999-05-11 2002-06-12 奥森泰克公司 用来创建合成指纹图象的方法和设备
CN1588425A (zh) * 2004-07-15 2005-03-02 清华大学 多注册指纹融合方法
CN102708360A (zh) * 2012-05-09 2012-10-03 深圳市亚略特生物识别科技有限公司 一种指纹模板生成及自动更新的方法

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