Biological information processing method, biological information identification method and related equipment

Abstract

The embodiment of the invention discloses a biological information processing method, a biological information identification method, a biological information identification device, equipment, a medium and a computer program product. The biological information processing method comprises the following steps: acquiring real-time behavior data of a plurality of verified users; sorting each verification user based on the real-time behavior data to obtain a first comparison sequence; sorting the plurality of verification templates of each verification user based on the real-time behavior data to obtain a second comparison sequence; and sorting based on the first comparison sequence and the second comparison sequence to generate a total comparison sequence. According to the method, the comparison position is increased, the common users and the common fingerprint templates are subjected to priority ranking, and sequential keep-alive ranking is carried out according to the user activeness and the fingerprint templates, so that a rapid comparison effect is realized during subsequent fingerprint identification, and the user experience is improved. The problems that in the prior art, full-amount comparison is needed during fingerprint recognition, so that the comparison workload is large, and much time is consumed are solved, and therefore the recognition efficiency and accuracy are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of biometric identification technology, and in particular to a biometric information processing method, a biometric information identification method, a device, a equipment, a medium and a computer program product. Background Art

[0002] Smart home is a modern residential system based on traditional residences and assisted by Internet of Things communication technology, automatic control technology and artificial intelligence technology. With the increasing popularity of smart furniture, it has brought many conveniences to people's lives and can provide users with a good, comfortable and intelligent living environment. In smart homes, biometric technology is widely used.

[0003] At present, the biometric technologies used in smart homes mainly include palm vein recognition, face recognition and fingerprint recognition, but due to the cost, memory, insufficient computing power and other factors, the biometric recognition time of most products on the market is relatively long, and when there is too much user data and capacity, the recognition response time will be even longer, seriously affecting the user experience. In addition, in terms of the success rate of biometric recognition, the existing technology generally requires all template libraries under each user name to be compared and recognized, resulting in a large workload and a long time consumption, and a low recognition rate, which further affects the user experience. Summary of the invention

[0004] In view of this, the present invention provides a biometric information processing method, a biometric information identification method, a device, an equipment, a medium and a computer program product, which are used to solve the problems of long fingerprint identification time and low identification rate in the prior art. In order to achieve one or part or all of the above purposes or other purposes, the present invention proposes a biometric information processing method, a biometric information identification method, a device, an equipment, a medium and a computer program product.

[0005] A first aspect: A biological information processing method, comprising:

[0006] Obtain real-time behavior data of multiple verified users;

[0007] Sort each of the verified users based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users;

[0008] Sorting multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user; the verification template is a fingerprint template pre-entered by the verification user;

[0009] Sorting is performed based on the first alignment order and the second alignment order to generate a total alignment order.

[0010] A second aspect: A biometric information recognition method, characterized by comprising:

[0011] Collecting a fingerprint to be identified and obtaining fingerprint features corresponding to the fingerprint to be identified;

[0012] The fingerprint features are matched based on the total comparison order to obtain a fingerprint recognition result.

[0013] A third aspect: A biological information processing device, comprising:

[0014] A data acquisition module is used to acquire real-time behavior data of multiple verified users;

[0015] A user sorting module, used to sort each of the verified users based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users;

[0016] A template sorting module, used to sort multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user; the verification template is a fingerprint template pre-entered by the verification user;

[0017] The fingerprint sorting module is used to sort based on the first comparison order and the second comparison order to generate a total comparison order.

[0018] A fourth aspect: A biometric information recognition device, comprising:

[0019] A fingerprint collection module is used to collect the fingerprint to be identified and obtain the fingerprint features corresponding to the fingerprint to be identified;

[0020] The fingerprint recognition module is used to match the fingerprint features based on the total comparison order to obtain a fingerprint recognition result.

[0021] A fifth aspect: An electronic device, comprising: at least one processor and at least one memory, wherein:

[0022] The memory stores program instructions or codes;

[0023] The program instructions or codes are loaded and executed by the processor, so that the device implements the biological information processing method as described in the first aspect or the biological information identification method as described in the second aspect.

[0024] A sixth aspect: A storage medium storing a computer program that can be loaded by a processor and execute the biological information processing method as described in the first aspect or the biological information identification method as described in the second aspect.

[0025] Aspect 7: A computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the biological information processing method as described in the first aspect or the biological information identification method as described in the second aspect.

[0026] Implementing the embodiments of the present invention will have the following beneficial effects:

[0027] First, the real-time behavior data of multiple verified users are obtained, and then each verified user is sorted according to the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users, and then multiple verification templates of each verified user are sorted to obtain a second comparison order for characterizing the template comparison order corresponding to each verified user, and finally the first comparison order and the second comparison order are combined to generate a total comparison order. The present invention prioritizes frequently used users and their frequently used fingerprint templates by improving the comparison position, and ranks them according to the user activity and fingerprint templates, thereby achieving a fast comparison effect in subsequent fingerprint recognition, avoiding the problem that the existing technology requires full comparison during fingerprint recognition, resulting in a large comparison workload and a lot of time, thereby effectively improving recognition efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] in:

[0030] Figure 1 An application environment diagram of the biological information processing method provided in the embodiment of the present application;

[0031] Figure 2 A schematic diagram of a biological information processing method provided in an embodiment of the present application;

[0032] Figure 3 A schematic diagram of a real-time update process provided by an embodiment of the present application;

[0033] Figure 4 A schematic diagram of a process for biometric information recognition provided in an embodiment of the present application;

[0034] Figure 5 A schematic diagram of the structure of a biological information processing device provided in an embodiment of the present application;

[0035] Figure 6 A schematic diagram of the structure of a biometric information recognition device provided in an embodiment of the present application;

[0036] Figure 7 This is a diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0040] Before further describing the embodiments of the present invention in detail, the nouns and terms involved in the embodiments of the present invention are described. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations.

[0041] The biological information processing method provided in this application can be applied to Figure 1 In the application environment shown. Figure 1 A biological information processing system is provided. The biological information processing system includes a smart device 100, a gateway 200 communicatively connected to the smart device 100, a router 300, a server 400, and a terminal 500.

[0042] The smart device 100 is connected to the gateway 200 in the bioinformation processing system, and communicates with the gateway 200 through its own configured communication module, and is then controlled by the gateway 200. In one embodiment, the smart device 100 is connected to the gateway 200 through a local area network path or a wide area network path, and is thus deployed in the gateway 200. The local area network may include ZIGBEE or Bluetooth, and the wide area network may include 2G / 3G / 4G / 5G / WIFI, etc.

[0043] The gateway 200 establishes a network connection with the terminal 500 or the server 400 through the router 300. In one embodiment, the gateway 200 and the terminal 500 may establish a network connection through a local area network or a wide area network path. The network connection interacts with the terminal 500, so that the user can control the smart device 100 connected to the gateway 200 to perform corresponding actions by means of the terminal 500 or the smart device 100.

[0044] Among them, the smart device 100 can be a smart camera, a smart curtain motor, a smart air conditioner, a smart door lock, a smart light, a smart TV, a smart printer, a smart sweeper, a smart robot, and can also be an electronic device such as a human body sensor, a door and window sensor, a temperature and humidity sensor, a water immersion sensor, a natural gas alarm, a smoke alarm, a wall switch, a wall socket, a wireless switch, a wireless wall switch, a magic cube controller, etc. equipped with a communication module. The terminal 500 can be a smart phone, a laptop, a personal computer, a tablet computer, an intelligent control panel, or other electronic device that can implement network connection, which is not limited here. The server 400 can be implemented by an independent server or a server cluster composed of multiple servers.

[0045] In the specific implementation process, the gateway 200 of the biometric information processing system can be first accessed through the smart device 100, and then the real-time behavior data of multiple verified users can be obtained through the smart device 100 deployed in the target space; each verified user is sorted based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users; multiple verification templates of each verified user are sorted based on the real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verified user; the verification template is a fingerprint template pre-entered by the verification user; the first comparison order and the second comparison order are sorted to generate a total comparison order.

[0046] In addition, the present application can also be implemented through hardware circuits or hardware circuits combined with software instructions. Therefore, the implementation of the present application is not limited to any specific hardware circuits, software, or a combination of the two.

[0047] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0048] See also Figure 2 A biological information processing method is provided, and the method is applied to an electronic device as an example for explanation. The electronic device may be Figure 1 The smart device, terminal, gateway, server, terminal, etc. in the present application are not limited to this. The biological information processing method specifically includes the following steps:

[0049] S1. Obtain real-time behavior data of multiple verified users;

[0050] Among them, the verified user is a user object that has successfully verified or entered a fingerprint template in advance. First, the real-time behavior data of multiple verified users is obtained, for example, by using firmware embedding or other data collection technologies to collect real-time behavior data of users using biometric unlocking of door locks.

[0051] Among them, real-time behavior data includes but is not limited to verification times, verification frequency, role information, verification results, hit templates, hit times and timestamps, among which, verification times are used to characterize the number of times a user attempts to verify; verification frequency is used to characterize the frequency of user verification within a specific time period; role information is used to characterize the identity or role of the user; verification results are used to characterize whether each verification is successful; hit templates are used to characterize the fingerprint template used when the user successfully verifies; hit times are used to characterize the number of times a specific template is successfully verified; and timestamps are used to characterize the time point at which each verification is recorded. Real-time behavior data can be obtained by collecting data in real time through fingerprint recognition devices or other biometric sensors. According to system requirements and user activity frequency, the collection frequency can be set to require continuous or periodic collection.

[0052] S2. Sort each verified user based on real-time behavior data to obtain a first comparison order for characterizing the comparison order of verified users;

[0053] Specifically, for step S2, information related to user verification behavior, such as the number of verifications, verification frequency timestamps, etc., is filtered out from the real-time behavior data, and statistical methods are used to analyze the user's behavior patterns to identify which verification users verify more frequently. The number of verifications of the user within the preset period is used as the main basis for sorting. The more verifications, the more frequently the user uses the system. The verifications of the verification users are sorted in descending order based on the number of verifications, that is, the verification users with the most verifications are ranked first, and finally a first comparison order is generated to characterize the priority order of each verification user when performing biometric identification. In the biometric identification system, according to the first comparison order, the system can first try to match verification users with high usage frequency, thereby speeding up the identification speed. By preferentially matching high-frequency users, the success rate of one-time identification can be increased.

[0054] S3. Sort multiple verification templates for each verified user based on real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verified user; the verification template is a fingerprint template pre-entered by the verification user;

[0055] Specifically, for step S3, the verification results of each verified user are extracted from the real-time behavior data, and the hit templates and hit times corresponding to each verified user are counted, that is, which verification templates are successfully matched during the verification process, and the hit times of each verification template; the verification templates corresponding to each verified user are sorted in descending order based on the hit times, and the verification templates with more hit times rank higher, and finally a second comparison order is formed to characterize the template comparison order corresponding to each verified user. In the biometric recognition process, the system will first try to match the top-ranked templates according to the second comparison order to achieve rapid recognition, and the overall recognition rate can be improved by preferentially matching templates with high success rates.

[0056] S4. Sorting based on the first comparison order and the second comparison order to generate a total comparison order;

[0057] Specifically, for step S4, the obtained first comparison order and second comparison order are comprehensively sorted, and the second comparison order of each verified user is associated with the position of the verified user's ranking in the first comparison order, thereby generating a total comparison order.

[0058] It can be seen that the biometric information processing method provided in this embodiment reduces the amount of data that the system needs to traverse during the recognition process by giving priority to matching frequently used users and verification templates, thereby speeding up the recognition speed; and gives priority to the verification users and verification templates that are most likely to be successfully verified, further improving the success rate of a single recognition. At the same time, since a full comparison of all users and templates is avoided, the consumption of computing resources and time is effectively reduced, thereby improving the efficiency of biometric information processing.

[0059] In some embodiments, Figure 3 As shown, the biological information processing method specifically also includes:

[0060] S51. If the number of verification templates corresponding to any user is detected to reach a preset first threshold, the historical reporting data of the fingerprint recognition device is obtained;

[0061] S52. Based on the historical reported data, determine the verification user and verification template corresponding to each time period;

[0062] S53. Use the verification template corresponding to each time period as the first verification template in the template comparison sequence corresponding to the verification user.

[0063] Specifically, the biometric information processing method provided in this embodiment may also include a real-time update step, by periodically monitoring and detecting the number of verification templates of each verified user. If it is detected that the number of verification templates of a certain verified user reaches or exceeds a preset first threshold, the historical reported data of the fingerprint recognition device is obtained, including but not limited to historical recognition records and user behavior patterns and other data. Based on the historical reported data, the verified users and the hit verification templates corresponding to each time period are analyzed, and the corresponding verification template in each time period is used as the first verification template in the template matching order corresponding to the verified user, that is, these verification templates are given a higher priority, so as to achieve priority matching of the verification templates that are most likely to be used during the peak period of user behavior. Through the above adjustment, the fingerprint recognition device can respond quickly during the peak period of user use, thereby improving the recognition speed and accuracy.

[0064] In a specific embodiment, assume that there are currently four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example, the fingerprint templates entered by user A are A1, A2, A3, and A4; the fingerprint templates entered by user B are B1, B2, B3, and B4; the fingerprint templates entered by user C are C1, C2, C3, and C4; the fingerprint templates entered by user D are D1, D2, D3, and D4. The user's verification template quantity threshold (preset first threshold) can be set to 4 to trigger the acquisition of historical data and the update of template sorting.

[0065] When it is detected that the number of verification templates corresponding to user A and user B reaches the preset first threshold. For example, user A has entered 4 templates, and user B has entered 5 templates, the historical reporting data of the fingerprint recognition device is obtained, which includes past verification records, usage frequency, successfully matched templates, etc. Based on the historical data, the system analyzes and determines the most active users and their most commonly used templates in each time period. For example: in the morning from 7:00 to 9:00, user A is the most active, and the most commonly used template is A2; in the afternoon from 12:00 to 14:00, user B is the most active, and the most commonly used template is B3; in the evening from 18:00 to 20:00, user C is the most active, and the most commonly used template is C4.

[0066] According to the analysis results of the time period, the template comparison order of each user is updated, and the most commonly used templates in the most active time period are placed first. The updated order may be as follows: User A: A2>A1>A3>A4; User B: B3>B1>B2>B4; User C: C4>C1>C2>C3; The number of templates for user D does not reach the threshold, so its template order is not updated and the original order is maintained.

[0067] During fingerprint recognition, the system will match according to the updated template comparison order. For example, in the morning time period, the system will first try to match user A's template A2. If the match fails, it will try A1, A3, and A4 in sequence. In the noon time period, the system will first try to match user B's template B3. If the match fails, it will try B1, B2, and B4 in sequence. In the evening time period, the system will first try to match user C's template C4. If the match fails, it will try C1, C2, and C3 in sequence.

[0068] In some embodiments, Figure 3 As shown, the biological information processing method specifically also includes:

[0069] S54. If it is detected that the number of verified users reaches the preset second threshold, the historical reporting data of the fingerprint recognition device is obtained;

[0070] S55. Based on the historical reported data, determine the corresponding verification user for each time period;

[0071] S56. Take the verified user corresponding to each time period as the first verified user in the first comparison sequence.

[0072] Specifically, the biometric information processing method provided in this embodiment can also update the steps in real time, by periodically monitoring and detecting the number of verified users. If it is detected that the number of stored or entered verified users reaches or exceeds the preset second threshold, the historical reported data of the fingerprint recognition device is obtained, including but not limited to historical recognition records and user behavior patterns, etc., and the verified users corresponding to each time period are analyzed based on the historical reported data, so that one of your verified users in each time period is used as the first verified user in the first comparison order, that is, these verified users are given a higher priority in the identification process, which helps to quickly identify users who are more active or more likely to be verified in a specific time period when the number of users is large. Through the above adjustment, the fingerprint recognition device can more effectively process user verification requests by giving priority to the verification requests of active users, reducing the amount of calculation in the biometric information identification process and improving processing efficiency.

[0073] In a specific embodiment, it is assumed that there are four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example: user A has entered fingerprint templates A1 and A2, user B has entered fingerprint templates B1 and B2, user C has entered fingerprint templates C1 and C2, and user D has entered fingerprint templates D1 and D2; first, a number of verified users is set (preset second threshold), for example, 4 users. When the number of verified users registered in the system reaches or exceeds this threshold, information is obtained from the historical reporting data of the fingerprint recognition device, including the number of user identifications, the most commonly used time period, the frequency of successful identification, etc.; based on historical data, the most active users in each time period are analyzed. For example: in the morning from 7:00 to 9:00, user A is the most active; at noon from 12:00 to 14:00, user B is the most active; in the evening from 18:00 to 20:00, user C is the most active; in the middle of the night from 23:00 to 01:00, user D is the most active. According to the analysis results, the first comparison order is updated to place the most active user in each time period as the first verified user in that time period. For example, the updated order is: 7:00-9:00 in the morning: A>B>C>D; 12:00-14:00 in the afternoon: B>A>C>D; 18:00-20:00 in the evening: C>A>B>D; 23:00-01:00 at night: D>A>B>C.

[0074] During fingerprint recognition, matching is performed according to the updated first comparison order. For example, in the morning time period, the system will first try to match the fingerprint template of user A. If the fingerprint template of user A fails to match, the fingerprint templates of users B, C, and D will be tried in sequence.

[0075] In some embodiments, step S2 "sorting each verified user based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users" may specifically include:

[0076] S21. Extract the number of verifications of each verified user within a preset period in the real-time behavior data;

[0077] S22. Based on the number of verifications, sort the comparison times of each verified user in descending order to obtain a first comparison order.

[0078] In a specific embodiment, for step S2, the collected real-time behavior data is used to construct a user behavior database through a statistical analysis method, and the database is used to store and analyze user behavior patterns. On the basis of the user behavior database, multiple verifications are sorted according to the number of times the verified user is identified. The more times a user is identified, the higher the frequency of use, and therefore the higher the ranking in the sorting. Based on the above-mentioned rough sorting strategy, a first comparison order is generated, and the users are sorted in descending order according to the number of verifications, ensuring that the system first considers those users with the highest frequency of use during the identification process. This embodiment reduces the number of users that the system needs to traverse during the identification process by giving priority to users with high frequency of use, thereby speeding up the identification speed, and first attempts to match those users who are more likely to be successfully verified, effectively improving the success rate of one-time identification.

[0079] In a specific embodiment, it is assumed that there are four users: A, B, C, and D. By recording the verification behavior of each user within a preset period (for example, in the past 30 days). The following is an example of the number of verifications for each user: User A has 50 verifications, User B has 30 verifications, User C has 20 verifications, and User D has 10 verifications. The number of verifications for each user within the preset period is extracted from the real-time behavior data, including counting the number of times each user attempts to verify, regardless of whether the verification is successful or failed. The number of verifications for each user is used as the main basis for sorting. The higher the number of verifications for the user, the higher the frequency of use. The users are sorted in descending order based on the number of verifications, that is, the user with the most verifications will be ranked first, and the user with the least number of verifications will be ranked last. According to the results of the descending order, a first comparison order is generated, such as user A (50 times), user B (30 times), user C (20 times), and user D (10 times).

[0080] During fingerprint recognition, users are matched according to the first comparison order. Since user A has the most verification times, which means he is the most frequent user, we first try to match the fingerprint of user A. If the fingerprint of user A is successfully matched, the verification process ends; if it fails, we continue to try to match the next user, that is, user B, and so on.

[0081] In some embodiments, step S3 "sorting multiple verification templates of each verification user based on real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user" may specifically include:

[0082] S31 extracts all verification results of each verified user in the real-time behavior data;

[0083] S32. Count the hit template and hit times corresponding to each verified user based on the verification results;

[0084] S33. Based on the hit templates and the hit times, multiple verification templates are sorted in descending order to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user.

[0085] Specifically, for step S3, after collecting the user's real-time behavior data, this includes information such as verification results, hit templates, and hit counts, where the verification result refers to the feedback result of the fingerprint recognition device after the user performs the fingerprint recognition operation, indicating whether the verification is successful or failed; the hit template refers to the fingerprint template actually used to match and successfully identify the user's identity during the user verification process; the hit count refers to the number of times a specific fingerprint template successfully matches and verifies the user's identity; extract all the verification results of each verified user in the real-time behavior data, and count the hit templates and hit counts corresponding to each user; according to the number of hits obtained by statistics, the verification templates of each user are sorted in descending order, and the templates with more hit counts will get higher priority. Based on the above sorting strategy, a second comparison order is generated, which will be used to guide the matching order of templates during the recognition process. This embodiment reduces the number of templates that the system needs to try during the recognition process by giving priority to matching templates with high hit counts, thereby speeding up the recognition speed. And because the templates that are more likely to be successfully verified are first tried, the success rate of one-time recognition is effectively improved.

[0086] In some embodiments, step S1 “obtaining real-time behavior data of multiple verified users” may specifically include:

[0087] S11. Collecting real-time behavior data of multiple verified users through a fingerprint recognition device, wherein the real-time behavior data includes one or more of the number of verifications, verification frequency, role information, verification results, hit templates, hit times and timestamps;

[0088] S12. Perform statistical analysis based on the real-time behavior data of multiple verified users to build a user behavior database.

[0089] Specifically, for step S1, the user's biometric data and real-time behavior data are collected in real time through a fingerprint recognition device or other biometric recognition sensor, wherein the real-time behavior data includes but is not limited to one or more of the following: verification times, verification frequency, role information, verification results, hit templates, hit times, and timestamps; wherein, verification times refers to the total number of times a user attempts to use his or her biometrics (such as fingerprints) for identity authentication, verification frequency refers to the number of times a user performs biometric verification within a specific time period, and role information refers to additional information related to the user's identity, such as the user's authority level; verification results refer to the feedback results of the fingerprint recognition device after the user performs a fingerprint recognition operation, indicating whether the verification is successful or failed, hit templates refer to the fingerprint templates actually used to match and successfully identify the user's identity during the user verification process, hit times refer to the number of times a specific fingerprint template successfully matches and verifies the user's identity, and timestamps refer to data recording the specific time point at which the verification event occurs; the collected real-time behavior data is continuously statistically analyzed to identify patterns and trends in user behavior. Using the results of the statistical analysis, a user behavior database is constructed, which is used to store user behavior information and provide data support for subsequent user and template sorting. In addition, the user behavior database needs to be updated regularly or in real time to reflect the latest changes in user behavior.

[0090] This embodiment provides a data basis for subsequent data-driven decision-making through analysis of real-time behavioral data, supports more effective user and template sorting, and thus improves recognition speed; in addition, the real-time updated user behavior database enables the system to adapt to changes in user behavior, thereby improving the flexibility of the system.

[0091] See also Figure 4 A biometric information recognition method is provided, and the method is applied to an electronic device as an example for explanation. The electronic device may be Figure 1 The biometric information recognition method specifically includes the following steps:

[0092] S10. Collect the fingerprint to be identified and obtain the fingerprint features corresponding to the fingerprint to be identified;

[0093] S20. Match the fingerprint features based on the total comparison order to obtain a fingerprint recognition result.

[0094] Specifically, the biometric information recognition method provided in this embodiment first uses a fingerprint recognition device to collect a fingerprint image of a user; extracts fingerprint features from the collected fingerprint image, and the fingerprint features include but are not limited to the direction, frequency, nodes, bifurcation points, etc. of the ridges; uses a first comparison sequence and a second comparison sequence constructed according to a user behavior database to form a total comparison sequence; according to the total comparison sequence, matches the extracted fingerprint features with the templates stored in the database, and finally generates a fingerprint recognition result based on the matching result, thereby determining whether the fingerprint verification of the current user is successful or failed.

[0095] This embodiment can quickly locate the verification user and the corresponding verification template that are most likely to be successfully matched by applying the total comparison order, thereby accelerating the recognition speed; by preferentially matching high-priority templates, the success rate of one-time recognition can be increased, thereby improving the user experience.

[0096] In some embodiments, the total comparison order includes a first comparison order and a second comparison order, and step S20 "matching fingerprint features based on the total comparison order to obtain a fingerprint recognition result" may specifically include:

[0097] S201. Match the fingerprint features based on the first comparison order to obtain a user matching result,

[0098] S202. Perform secondary matching on the fingerprint features based on the user matching result and the second comparison order to obtain a fingerprint recognition result.

[0099] Specifically, first use the fingerprint recognition device to collect the user's fingerprint image, and extract key fingerprint features from the collected fingerprint image; according to the user's real-time behavior data and usage mode, sort the verification users according to the first comparison order to determine the user to be matched first; match the extracted fingerprint features with the verification template of the verification user ranked first to generate a user matching result; if the match in the first comparison order is unsuccessful or further verification is required, the fingerprint features will be matched again according to the second comparison order. The second comparison order is based on the matching accuracy and frequency of the verification template of the verification user. The fingerprint features are matched more carefully through the second comparison order to determine the verification template matching result corresponding to the verification user. According to the matching results of the first comparison order and the second comparison order, the fingerprint recognition result is finally determined to judge whether the verification is successful or failed.

[0100] In a specific embodiment, it is assumed that there are four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example: user A has entered fingerprint templates A1 and A2, user B has entered fingerprint templates: B1 and B2, user C has entered fingerprint templates C1 and C2, and user D has entered fingerprint templates D1 and D2; first, matching is performed based on the first comparison order, which is obtained based on behavioral data such as the number of user verifications and verification frequency, and priority is given to matching users who are most likely to be successfully verified. For example, users are ranked according to their activity: user A (most active), user B, user C, and user D; the features of the fingerprint to be identified are extracted, and attempts are made to match them with fingerprint templates A1 and A2 of user A. If the template of user A is successfully matched, the identification process ends and the system records the successful verification. If the template of user A is unsuccessful, the next user, user B, is tried to be matched according to the first comparison order, and so on. After obtaining the user matching result, a secondary match is performed based on the second comparison order. The second comparison order is obtained based on the number of hits and matching accuracy of the corresponding template of each user, and is used for further confirmation after the user match is successful, or to try other templates after the user match is unsuccessful. For example, if the template match of user A is unsuccessful, the system will perform a secondary match based on the second comparison order of user B (which may be sorted based on the number of hits of templates B1 and B2 of user B). If a successfully matched template is found in the second comparison order, the system records the successful verification and may update the first comparison order and the second comparison order to reflect the successful match. If all matching attempts fail, the system records the verification failure and takes appropriate measures as needed, such as denying access or requiring re-verification.

[0101] This embodiment combines the first comparison order and the second comparison order to perform two-level sorting and matching, which can more accurately identify users and reduce the possibility of misidentification; prioritize matching high-priority users and templates, reduce the amount of calculation in the recognition process, improve recognition efficiency, and thus improve user experience.

[0102] In some embodiments, step S202 "perform secondary matching on the fingerprint features based on the user matching result and the second comparison order to obtain the fingerprint recognition result" may specifically include:

[0103] If the user matching result is detected to be a successful match with any verified user in the first comparison order, a second match is performed on the fingerprint features based on the second comparison order to obtain a fingerprint recognition result;

[0104] If it is detected that the user matching result is unsuccessful matching with any verified user in the first comparison sequence, a user fingerprint query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a first query result, and a fingerprint recognition result is determined based on the first query result.

[0105] Specifically, for step S62, after preliminary matching based on the first comparison order, the system will detect whether the user matching result is successful. If the user matching result is unsuccessful, that is, no user template in the first comparison order is matched successfully, a secondary matching process will be triggered, and the fingerprint features will be queried through a pre-built fingerprint template library to find possible matching templates, thereby generating a first query result, which may include one or more possible matching templates; the final fingerprint recognition result is determined based on the first query result, if the first query result is a successful match, the fingerprint recognition result is determined to be a successful verification, and the first comparison ranking is updated based on this result; if the first query result is an unsuccessful match, the fingerprint recognition result is determined to be a failed verification; if the secondary match is successful, the relevant comparison ranking information is updated to subsequently improve the recognition efficiency.

[0106] In a specific embodiment, it is assumed that there are four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example: user A has entered fingerprint templates A1 and A2, user B has entered fingerprint templates: B1 and B2, user C has entered fingerprint templates C1 and C2, and user D has entered fingerprint templates D1 and D2; first, the fingerprint features of user A are tried to be matched according to the first comparison order. Assuming that the system detects that the fingerprint features of user A successfully match template A1, the fingerprint features of user A are then matched again based on the second comparison order. The second comparison order may be sorted according to the number of hits of the template. Assuming that A1 has the highest number of hits, A1 is confirmed as the template that finally matches successfully. This successful match is recorded, and the relevant user and template sorting information is updated so that user A can be identified faster in the future. If the fingerprint features of user A do not match all templates in the first comparison order, the query phase will be entered, and the fingerprint features will be queried through the pre-built fingerprint template library to find other templates that may match, including other templates A2 of user A, and templates of other users. At this time, the first query result is generated, including one or more possible matching templates. Based on the first query result, the final fingerprint recognition result is determined. If the first query result shows a successful match (for example, template A2 matches the fingerprint feature), the successful match is recorded, and the second comparison order of user A is updated to improve the ranking of A2. If the first query result shows an unsuccessful match, the fingerprint recognition result is determined to be a verification failure, and appropriate measures are taken as needed, such as denying access or requiring re-verification.

[0107] This embodiment effectively improves the accuracy of biometric information recognition by performing a secondary match when the first comparison sequence is unsuccessful; even if the initial match is unsuccessful, the recognition result can be determined by querying the template library, thereby enhancing the robustness of the system. At the same time, through targeted secondary matching, computing resources can be used more effectively to avoid unnecessary full library searches.

[0108] In some embodiments, the step of “determining the fingerprint recognition result based on the first query result” may specifically include:

[0109] If it is detected that the first query result is a successful match, the fingerprint recognition result is determined to be a successful verification, and the first comparison ranking is updated based on the first query result;

[0110] If it is detected that the first query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

[0111] Specifically, after performing a second match through the second comparison order, the first query result is analyzed to determine whether there is a successful matching template. If the first query result indicates a successful match, the fingerprint recognition result is determined to be a successful verification, and the first comparison order is updated according to the first query result to improve efficiency and accuracy in the subsequent recognition process. If the first query result indicates an unsuccessful match, that is, the corresponding verification template cannot be matched, the fingerprint recognition result is determined to be a verification failure, and the user can be subsequently unlocked or denied access. In addition, detailed information on the recognition attempt, including success or failure results, can also be recorded for subsequent analysis and system optimization.

[0112] In a specific embodiment, it is assumed that there are four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example: user A has entered fingerprint templates A1 and A2, user B has entered fingerprint templates: B1 and B2, user C has entered fingerprint templates C1 and C2, and user D has entered fingerprint templates D1 and D2; first, try to match the user's fingerprint features according to the first comparison order. Assume that the first comparison order is sorted based on the number of verifications of the user, as follows: user A (the most verifications), user B, user C, user D; if the initial match is unsuccessful, the user's fingerprint features will be queried to find other templates that may match. The query may include another template A2 of user A. If the first query result is a successful match, it is found that the A2 template successfully matches the fingerprint feature, and the fingerprint recognition result is determined to be a successful verification, and the ranking of user A is promoted because another template of user A is also successfully matched. For example, the updated first comparison order is as follows: user A (both A1 and A2 are taken into account), user B, user C, user D. If the first query result is a match failure, and no template is found to successfully match the fingerprint feature in the query, the fingerprint recognition result is determined to be a verification failure, and the failed attempt is recorded, and measures are taken as needed, such as requiring the user to re-verify or use other verification methods. If user A's A2 template is successfully matched in the first query, the system will update the first comparison order by increasing the number of user A's verifications or adjusting the priority of the template. If user A's A2 template is unsuccessful, keep the current order, or adjust the algorithm parameters based on the failed attempt.

[0113] This embodiment can determine the recognition result more accurately through evaluation based on the first query result, and can update the ranking after a successful match, so as to adaptively optimize the subsequent recognition process.

[0114] In some embodiments, the step of “performing a second match on the fingerprint features based on the second comparison order to obtain a fingerprint recognition result” may specifically include:

[0115] Perform secondary matching on the fingerprint features based on the second comparison order to obtain a fingerprint matching result;

[0116] If the fingerprint matching result is detected as a successful match, the user's fingerprint verification is determined to be successful, and the hit template and hit count corresponding to the fingerprint recognition result are updated;

[0117] If it is detected that the fingerprint matching result is an unsuccessful match, a fingerprint template query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a second query result, and a fingerprint recognition result is determined based on the second query result.

[0118] Specifically, when the matching of the first comparison order fails to successfully identify the user, the fingerprint features are matched again according to the second comparison order, wherein the second comparison order is sorted based on the matching accuracy and frequency of the user's verification template, and is used to guide the secondary matching process; the collected fingerprint features are matched with the templates in the second comparison order to obtain the secondary matching results; by analyzing the secondary matching results, it is determined whether there is a template that successfully matches the collected fingerprint features. If the secondary match is successful, that is, a matching template is found, the user's fingerprint verification is determined to be successful, and the hit template and the number of hits are updated to improve the subsequent comparison order and recognition efficiency. If the secondary match is unsuccessful, that is, no matching template is found, the fingerprint features are further queried through the pre-built fingerprint template library to generate a second query result, including an alternative matching template or a mark of a failed match; based on the second query result, the final fingerprint recognition result is determined, and corresponding user feedback is given.

[0119] In a specific embodiment, there are four users: A, B, C, and D, and each user has entered multiple fingerprint templates. For example: user A has entered fingerprint templates A1 and A2, user B has entered fingerprint templates: B1 and B2, user C has entered fingerprint templates C1 and C2, and user D has entered fingerprint templates D1 and D2; first, try to match the user's fingerprint features according to the first comparison order. Assume that the initial match fails, that is, no template matches the fingerprint feature. Perform a secondary match on the fingerprint features according to the second comparison order. The second comparison order can be sorted based on the number of template hits or other relevant indicators. Assume that in the secondary match, it is found that user A's template A1 successfully matches the fingerprint feature, and it is determined that user A's fingerprint verification is successful, and user A's hit template (A1) and hit count are updated. For example, if A1's previous hit count was 5 times, it is now increased to 6 times. If the secondary match is also unsuccessful, that is, no template matches the fingerprint feature, the fingerprint feature is queried through the pre-built fingerprint template library to find other templates that may match, and a second query result is generated, including one or more possible matching templates, or a mark of failed matching. Based on the second query result, the final fingerprint recognition result is determined: If the second query result shows a successful match, the verification is determined to be successful, and the relevant hit templates and hit counts are updated. If the second query result shows an unsuccessful match, the verification is determined to have failed, and measures are taken as needed, such as requiring the user to re-verify or use other verification methods. If the secondary match or the second query is successful, the first comparison order and the second comparison order are updated to reflect the latest matching information and user behavior.

[0120] This embodiment increases the chance of identifying the correct user through secondary matching, especially when the first matching fails. Even if the initial matching fails, the system can provide accurate recognition results through secondary matching to improve user satisfaction. In addition, by updating the hit template and the number of times after a successful match, the subsequent recognition process can be adaptively optimized.

[0121] In some embodiments, the step of “determining the fingerprint recognition result based on the second query result” may specifically include:

[0122] If it is detected that the second query result is a successful match, the fingerprint recognition result is determined to be a successful verification, and the second comparison ranking is updated based on the second query result;

[0123] If it is detected that the second query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

[0124] Specifically, when the secondary matching fails to directly obtain the recognition result, a query is performed through the fingerprint template library to generate a second query result. If the second query result indicates that the match is successful, that is, a template matching the fingerprint feature is found in the template library, the fingerprint recognition result is determined to be a successful verification, and the second comparison order is updated based on the second query result, and the sorting position of the verification template in the second comparison order is adjusted to improve the recognition efficiency in the subsequent recognition process. If the second query result indicates that the match is unsuccessful, that is, no matching template is found in the template library, the fingerprint recognition result is determined to be a verification failure, and the user is given corresponding feedback, including unlock authorization or access denial.

[0125] This embodiment determines the recognition result more accurately through the evaluation of the second query result, reduces the possibility of misrecognition, updates the ranking after a successful match, and can adaptively optimize the subsequent recognition process.

[0126] It should be understood that although Figure 2-Figure 4 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-Figure 4 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0127] In order to facilitate better implementation of the biological information processing method of the embodiment of the present application, the embodiment of the present application also provides a biological information processing device based on the above biological information processing method. The meanings of the terms are the same as those in the above biological information processing method, and the specific implementation details can refer to the description in the method embodiment.

[0128] See also Figure 5 , Figure 5 20 is a schematic diagram of the structure of a biometric information processing device provided in an embodiment of the present application. The biometric information processing device includes a data acquisition module 201, a user sorting module 202, a template sorting module 203 and a fingerprint sorting module 204. Specifically, it can be as follows:

[0129] The data acquisition module 201 is used to acquire real-time behavior data of multiple verified users;

[0130] Specifically, for the data acquisition module 201, the verified user is a user object that has successfully verified or entered a fingerprint template in advance. First, the real-time behavior data of multiple verified users is obtained, for example, by using firmware embedding or other data collection technologies to collect real-time behavior data of users using biometric unlocking of door locks.

[0131] A user sorting module 202, used to sort each verified user based on the real-time behavior data to obtain a first comparison order for representing the comparison order of the verified users;

[0132] Specifically, for the user sorting module 202, information related to user verification behavior, such as verification times, verification frequency timestamps, etc., is screened out from the real-time behavior data, and statistical methods are used to analyze the user's behavior pattern to identify which verification users perform verification more frequently. The number of verifications of the user within a preset period may be used as the main basis for sorting. The more verifications, the more frequently the user uses the system. Therefore, the verification users are sorted in descending order based on the number of verifications, that is, the verification users with the most verifications are ranked first, and finally a first comparison order is generated to characterize the priority order of each verification user when performing biometric identification.

[0133] The template sorting module 203 is used to sort multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for representing the template comparison order corresponding to each verification user; the verification template is a fingerprint template pre-entered by the verification user;

[0134] Specifically, for the template sorting module 203, the verification results of each verified user are extracted from the real-time behavior data, and the hit templates and hit times corresponding to each verified user are counted, that is, which verification templates are successfully matched during the verification process, and the matching frequency of each verification template; based on the hit times, the verification templates corresponding to each verified user are sorted in descending order, and the verification templates with more hit times are ranked higher, and finally a second comparison order is formed, which is used to characterize the template comparison order corresponding to each verified user.

[0135] Fingerprint sorting module 204, used to sort based on the first comparison order and the second comparison order to generate a total comparison order;

[0136] Specifically, the fingerprint sorting module 205 comprehensively sorts the obtained first comparison order and second comparison order, and associates the second comparison order of each verified user with the position of the verified user's ranking in the first comparison order, thereby generating a total comparison order.

[0137] In some embodiments, the biological information processing apparatus further includes a first updating module, which is used to:

[0138] If it is detected that the number of verification templates corresponding to any user reaches a preset first threshold, the historical reporting data of the fingerprint recognition device is obtained;

[0139] Based on historical reporting data, determine the verification users and their verification templates corresponding to each time period;

[0140] The verification template corresponding to each time period is used as the first verification template in the template comparison sequence corresponding to the verification user.

[0141] In some embodiments, the biological information processing apparatus further includes a second updating module, which is used to:

[0142] If it is detected that the number of verified users reaches a preset second threshold, obtaining historical reported data of the fingerprint recognition device;

[0143] Based on historical reported data, determine the verification users corresponding to each time period;

[0144] The verified user corresponding to each time period is taken as the first verified user in the first comparison sequence.

[0145] In some embodiments, the user sorting module 202 may specifically include:

[0146] A first extraction unit is used to extract the number of verifications of each verified user within a preset period in the real-time behavior data;

[0147] The user sorting unit is used to sort each verified user in descending order of the number of comparisons based on the number of verifications to obtain a first comparison order.

[0148] In some embodiments, the template sorting module 203 may specifically include:

[0149] A second extraction unit is used to extract all verification results of each verified user in the real-time behavior data;

[0150] A statistics unit, used to count the hit templates and hit times corresponding to each verified user based on the verification results;

[0151] The template sorting unit is used to sort the multiple verification templates in descending order based on the hit templates and the hit times, so as to obtain a second comparison order for representing the template comparison order corresponding to each verification user.

[0152] In some embodiments, the data acquisition module 201 may specifically include:

[0153] A collection unit, used to collect real-time behavior data of multiple verified users through a fingerprint recognition device, wherein the real-time behavior data includes one or more of verification times, verification frequency, role information, verification results, hit templates, hit times and timestamps;

[0154] The analysis unit is used to perform statistical analysis based on the real-time behavior data of multiple verified users to build a user behavior database.

[0155] To summarize, the biometric information processing device provided in this embodiment prioritizes frequently used users and their frequently used fingerprint templates by improving the comparison position, and ranks them according to the user activity and fingerprint template, thereby achieving a fast comparison effect in subsequent fingerprint recognition, avoiding the problem of the prior art that full comparison is required during fingerprint recognition, resulting in a large comparison workload and a long time consumption, thereby effectively improving recognition efficiency and accuracy.

[0156] In order to facilitate better implementation of the biometric information recognition method of the embodiment of the present application, the embodiment of the present application also provides a biometric information recognition device based on the above biometric information recognition method. The meanings of the terms are the same as those in the above biometric information recognition method, and the specific implementation details can refer to the description in the method embodiment.

[0157] See also Figure 6 , Figure 6 30 is a schematic diagram of the structure of a biometric information recognition device provided in an embodiment of the present application. The biometric information recognition device includes a fingerprint collection module 301 and a fingerprint recognition module 302. Specifically, it can be as follows:

[0158] The fingerprint collection module 301 is used to collect the fingerprint to be identified and obtain the fingerprint features corresponding to the fingerprint to be identified;

[0159] The fingerprint recognition module 302 is used to match the fingerprint features based on the total comparison order to obtain a fingerprint recognition result.

[0160] In some embodiments, the total comparison sequence includes a first comparison sequence and a second comparison sequence, and the fingerprint recognition module 302 may specifically include:

[0161] A primary matching unit is used to match the fingerprint features based on the first comparison order to obtain a user matching result.

[0162] The secondary matching unit is used to perform secondary matching on the fingerprint features based on the user matching result and the second comparison order to obtain the fingerprint recognition result.

[0163] In some embodiments, the secondary matching unit is specifically used for:

[0164] If the user matching result is detected to be a successful match with any verified user in the first comparison order, a second match is performed on the fingerprint features based on the second comparison order to obtain a fingerprint recognition result;

[0165] If it is detected that the user matching result is unsuccessful matching with any verified user in the first comparison sequence, a user fingerprint query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a first query result, and a fingerprint recognition result is determined based on the first query result.

[0166] In some embodiments, the secondary matching unit is further used for:

[0167] If it is detected that the first query result is a successful match, the fingerprint recognition result is determined to be a successful verification, and the first comparison ranking is updated based on the first query result;

[0168] If it is detected that the first query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

[0169] In some embodiments, the secondary matching unit is further used for:

[0170] Perform secondary matching on the fingerprint features based on the second comparison order to obtain a fingerprint matching result;

[0171] If the fingerprint matching result is detected as a successful match, the user's fingerprint verification is determined to be successful, and the hit template and hit count corresponding to the fingerprint recognition result are updated;

[0172] If it is detected that the fingerprint matching result is an unsuccessful match, a fingerprint template query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a second query result, and a fingerprint recognition result is determined based on the second query result.

[0173] In some embodiments, determining the fingerprint recognition result based on the second query result includes:

[0174] If it is detected that the second query result is a successful match, the fingerprint recognition result is determined to be a successful verification, and the second comparison ranking is updated based on the second query result;

[0175] If it is detected that the second query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

[0176] To sum up, the biometric information recognition device provided in this embodiment can quickly locate the verification user and the corresponding verification template that are most likely to be successfully matched by applying the total comparison order, thereby speeding up the recognition speed; by preferentially matching high-priority templates, the success rate of one-time recognition can be increased, thereby improving the user experience.

[0177] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a target detection method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or it can be a computer device.

[0178] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0179] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0180] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0181] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0182] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0183] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0184] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A biological information processing method, characterized in that: include: Obtain real-time behavior data of multiple verified users; Sorting each of the verified users based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users; Sort multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for characterizing a template comparison order corresponding to each verification user; the verification template is a fingerprint template pre-entered by the verification user; Sorting is performed based on the first alignment order and the second alignment order to generate a total alignment order.

2. The biological information processing method according to claim 1, characterized in that: Also includes: If it is detected that the number of verification templates corresponding to any user reaches a preset first threshold, the historical reporting data of the fingerprint recognition device is obtained; Based on the historical reported data, determine the verification user and the verification template corresponding to each time period; The verification template corresponding to each time period is used as the first verification template in the template comparison sequence corresponding to the verification user.

3. The biological information processing method according to claim 1, characterized in that: Also includes: If it is detected that the number of verified users reaches a preset second threshold, obtaining historical reported data of the fingerprint recognition device; Determine the verified user corresponding to each time period based on the historical reported data; The verified user corresponding to each time period is taken as the first verified user in the first comparison sequence.

4. The biological information processing method according to claim 1, wherein: The step of sorting each of the verified users based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users includes: Extracting the verification times of each verified user within a preset period from the real-time behavior data; Based on the verification times, each of the verified users is sorted in descending order of the comparison times to obtain the first comparison order.

5. The biological information processing method according to claim 1, wherein: The step of sorting the multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user includes: Extracting all verification results of each of the verified users in the real-time behavior data; Based on the verification result, count the hit template and hit times corresponding to each verified user; Based on the hit template and the hit count, multiple verification templates are sorted in descending order to obtain a second comparison order for characterizing a template comparison order corresponding to each verification user.

6. The biological information processing method according to claim 1, wherein: The obtaining of real-time behavior data of multiple verified users includes: Collecting real-time behavior data of multiple verified users through a fingerprint recognition device, wherein the real-time behavior data includes one or more of verification times, verification frequency, role information, verification results, hit templates, hit times, and timestamps; A user behavior database is constructed based on statistical analysis of the real-time behavior data of the multiple verified users.

7. A method for identifying biological information, characterized in that: include: Collecting a fingerprint to be identified and obtaining fingerprint features corresponding to the fingerprint to be identified; The fingerprint features are matched based on the total comparison order to obtain a fingerprint recognition result.

8. The biological information recognition method according to claim 7, characterized in that: The total comparison sequence includes a first comparison sequence and a second comparison sequence, and matching the fingerprint features based on the total comparison sequence to obtain a fingerprint recognition result includes: Matching the fingerprint features based on the first comparison order to obtain a user matching result, The fingerprint feature is matched again based on the user matching result and the second comparison order to obtain a fingerprint recognition result.

9. The biological information recognition method according to claim 8, characterized in that: The performing secondary matching on the fingerprint feature based on the user matching result and the second comparison order to obtain a fingerprint recognition result includes: If it is detected that the user matching result is a successful match with any verified user in the first comparison order, a second matching is performed on the fingerprint feature based on the second comparison order to obtain a fingerprint recognition result; If it is detected that the user matching result is unsuccessful in matching with any verified user in the first comparison sequence, a user fingerprint query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a first query result, and a fingerprint recognition result is determined based on the first query result.

10. The biological information recognition method according to claim 9, characterized in that: The determining of the fingerprint recognition result based on the first query result includes: If it is detected that the first query result is a successful match, determining that the fingerprint recognition result is a successful verification, and updating the first comparison ranking based on the first query result; If it is detected that the first query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

11. The biological information recognition method according to claim 8, characterized in that: The performing secondary matching on the fingerprint features based on the second comparison order to obtain a fingerprint recognition result includes: Performing a secondary match on the fingerprint features based on the second comparison order to obtain a fingerprint matching result; If the fingerprint matching result is detected as a successful match, the user fingerprint verification is determined to be successful, and the hit template and hit count corresponding to the fingerprint recognition result are updated; If it is detected that the fingerprint matching result is an unsuccessful match, a fingerprint template query is performed on the fingerprint feature through a pre-built fingerprint template library to generate a second query result, and a fingerprint recognition result is determined based on the second query result.

12. The biological information recognition method according to claim 11, characterized in that: The determining the fingerprint recognition result based on the second query result includes: If it is detected that the second query result is a successful match, determining that the fingerprint recognition result is a successful verification, and updating the second comparison ranking based on the second query result; If it is detected that the second query result is a match failure, the fingerprint recognition result is determined to be a verification failure.

13. A biological information processing device, characterized in that: include: A data acquisition module, used to acquire real-time behavior data of multiple verified users; A user sorting module, used to sort each of the verified users based on the real-time behavior data to obtain a first comparison order for characterizing the comparison order of the verified users; A template sorting module, used to sort multiple verification templates of each verification user based on the real-time behavior data to obtain a second comparison order for characterizing the template comparison order corresponding to each verification user; the verification template is a fingerprint template pre-entered by the verification user; The fingerprint sorting module is used to sort based on the first comparison order and the second comparison order to generate a total comparison order.

14. A biometric information recognition device, characterized in that: include: A fingerprint collection module is used to collect the fingerprint to be identified and obtain the fingerprint features corresponding to the fingerprint to be identified; The fingerprint recognition module is used to match the fingerprint features based on the total comparison order to obtain a fingerprint recognition result.

15. An electronic device, characterized in that: include: at least one processor and at least one memory, wherein: The memory stores program instructions or codes; The program instructions or codes are loaded and executed by the processor, so that the device implements the biological information processing method according to any one of claims 1 to 6 or the biological information recognition method according to any one of claims 7 to 12.

16. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the fingerprint sorting method according to any one of claims 1 to 6 or the fingerprint identification method according to any one of claims 7 to 12.

17. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the steps of the biological information processing method according to any one of claims 1 to 6 or the biological information recognition method according to any one of claims 7 to 12.

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