Fingerprint identification control method

Abstract

The invention discloses a fingerprint identification control method, which comprises the following steps: S1, carrying out hardware optimization and optimizing a sensor technology, and has the beneficial effects that hardware of a fingerprint identification technology is optimized regularly, the sensor technology is optimized, an image is processed in cooperation, and a feature extraction algorithm is optimized, so that the fingerprint identification technology is optimized; according to the fingerprint identification method, the matching algorithm is improved and optimized, the robustness of the system is enhanced, and the data quality and diversity are improved, so that the precision of the fingerprint identification technology can be improved through the cooperation of the technologies, and the accuracy during fingerprint identification can be improved; besides, by improving regular system integration and optimization, regular testing, improvement of user interaction and feedback capability, improvement of security firewall and privacy protection and cooperation of multi-modal fusion, it is guaranteed that the fingerprint identification technology can always keep the highest optimization level, and the security storage performance of fingerprint data is improved; and the phenomenon of losing and stealing is prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of fingerprint recognition, and specifically to a fingerprint recognition control method. Background Art

[0002] Based on the uniqueness and stability of fingerprints, fingerprint recognition technology converts fingerprints into digital features through complex algorithms to achieve identity authentication. Its core principle lies in using the detailed feature points of fingerprints, including direction, curvature, and nodes, etc., and judging identity by comparing these feature points.

[0003] However, there are certain defects in fingerprint recognition control. When recognizing fingerprints, the fingerprint recognition technology has a phenomenon of low accuracy, which will cause the accuracy of fingerprint recognition to be too low when people use it, and thus affect the popularization of fingerprint recognition technology. Summary of the Invention

[0004] The purpose of the present invention is to provide a fingerprint recognition control method to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: A fingerprint recognition control method, including the following contents:

[0006] S1: Conduct hardware optimization and optimize sensor technology;

[0007] S2: Perform preprocessing on the image;

[0008] S3: Optimize the feature extraction algorithm and simultaneously improve and optimize the matching algorithm;

[0009] S4: Enhance the system robustness and improve the data quality and diversity;

[0010] S5: Improve the user interaction and feedback ability;

[0011] S6: Regularly conduct system integration and optimization, and simultaneously regularly conduct testing work;

[0012] S7: Improve the security firewall and privacy protection, and can cooperate with multimodal fusion.

[0013] Preferably, the step S1 includes the following contents:

[0014] S11: Improve the quality of the fingerprint recognition sensor, use a sensor with a higher resolution, and improve the accuracy of capturing fingerprint details;

[0015] S12: Select a sensor material with high wear resistance and anti-pollution to increase the service life;

[0016] S13: Adopt multi - spectral imaging technology to enhance multi - environmental adaptability.

[0017] Preferably, the following contents are included in the step S2:

[0018] S21: Perform pre - processing on the image, and improve the image quality through technologies such as filtering and contrast adjustment;

[0019] S22: Reduce noise interference to ensure the clarity of fingerprint features;

[0020] S23: And perform post - repair on the blurred or incomplete fingerprint image, repair the damaged or blurred areas to improve the recognition effect.

[0021] Preferably, the following contents are included in the step S3:

[0022] S31: Combine detailed features and global features to improve the recognition accuracy, and use deep learning technologies such as convolutional neural networks to set the function of automatically extracting effective features;

[0023] S32: Introduce multi - modal matching, combine multiple features for comprehensive judgment, and add a live detection function to prevent the phenomenon of forged fingerprints;

[0024] S33: And cooperate with the use of algorithms such as graph matching or local feature matching to improve the matching speed and accuracy, and dynamically adjust the matching threshold according to the environment to reduce misrecognition and rejection.

[0025] Preferably, the following contents are included in the step S4:

[0026] S41: Combine fingerprints with other biometric features to improve the overall performance of the system, and design algorithms suitable for different environments to ensure the stable operation of the system under various conditions;

[0027] S42: Decompose the system into multiple independent modules to isolate faults and reduce the impact on other parts of the system;

[0028] S43: Design a mechanism that can detect and handle errors to improve the fault tolerance rate.

[0029] Preferably, the following contents are included in the step S5:

[0030] S51: Provide a clear guiding program for fingerprint collection to ensure that users place their fingers correctly;

[0031] S52: Provide a real - time feedback function during the collection process to help users adjust the position of their fingers;

[0032] S53: Set up a real-time monitoring function for user feedback to ensure that problems can be discovered and processed in a timely manner, thereby improving the user experience.

[0033] Preferably, the step S6 includes the following contents:

[0034] S61: Optimize the collaborative work of hardware and software in a set cycle, reduce power consumption, and extend the battery life of the device;

[0035] S62: Regularly test the performance of the system and conduct self-check work. When problems are detected during self-check, repair the problems in a timely manner.

[0036] Preferably, the step S7 includes the following contents:

[0037] S71: Install a firewall protection for fingerprint recognition technology and encrypt and store fingerprint data to prevent fingerprint data from being stolen;

[0038] S72: Cooperate with the introduction of technologies such as live detection to prevent forged fingerprint attacks.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows: By regularly optimizing the hardware of fingerprint recognition technology, optimizing sensor technology, cooperating with image processing work, optimizing the feature extraction algorithm, improving and optimizing the matching algorithm, enhancing the system robustness, and improving data quality and diversity. Through the cooperation of the above technologies, the accuracy of fingerprint recognition technology can be improved, and the accuracy rate during fingerprint recognition can be increased; In addition, by improving system integration and optimization regularly, conducting regular tests, improving user interaction and feedback capabilities, enhancing security firewalls and privacy protection, and cooperating with multi-modal fusion, the fingerprint recognition technology can be ensured to always maintain the highest level of optimization, improve the secure storage performance of fingerprint data, prevent theft, and can be selectively combined with recognition and multi-modal fusion, so as to further improve the stability and accuracy of fingerprint recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] Please refer to Figure 1, the present invention provides a technical solution: a fingerprint recognition control method, including the following:

[0043] S1: Perform hardware optimization and optimize sensor technology;

[0044] S2: Perform preprocessing on the image;

[0045] S3: Optimize the feature extraction algorithm and simultaneously improve and optimize the matching algorithm;

[0046] S4: Enhance the system robustness and improve the data quality and diversity;

[0047] S5: Improve the user interaction and feedback ability;

[0048] S6: Regularly perform system integration and optimization and simultaneously regularly perform testing work;

[0049] S7: Improve the security firewall and privacy protection and can cooperate with multimodal fusion.

[0050] Among them, the step S1 includes the following:

[0051] S11: Improve the quality of the fingerprint recognition sensor, use a sensor with a higher resolution, and improve the accuracy of capturing fingerprint details;

[0052] S12: Select a sensor material with high wear resistance and anti-pollution to improve the service life;

[0053] S13: Adopt multispectral imaging technology to enhance the multi-environment adaptability.

[0054] Among them, the step S2 includes the following:

[0055] S21: Perform preprocessing on the image, and improve the image quality through techniques such as filtering and contrast adjustment;

[0056] S22: Reduce noise interference to ensure the clarity of fingerprint features;

[0057] S23: Perform post-repair on blurred or incomplete fingerprint images, repair damaged or blurred areas, and improve the recognition effect.

[0058] Among them, the step S3 includes the following:

[0059] S31: Combine the local features and global features to improve the recognition accuracy, and use deep learning technologies such as convolutional neural networks to set the function of automatically extracting effective features;

[0060] S32: Perform multimodal matching, make comprehensive judgments by combining multiple features, and add a liveness detection function to prevent the appearance of forged fingerprints;

[0061] S33: Use algorithms such as graph matching or local feature matching in combination to improve the matching speed and accuracy, and dynamically adjust the matching threshold according to the environment to reduce misidentifications and rejections.

[0062] Among them, the following are included in the step S4:

[0063] S41: Combine fingerprints with other biometric features to improve the overall performance of the system, and design algorithms adapted to different environments to ensure the stable operation of the system under various conditions;

[0064] S42: Decompose the system into multiple independent modules to isolate faults and reduce the impact on other parts of the system;

[0065] S43: Design a mechanism that can detect and handle errors to improve the fault tolerance rate.

[0066] Among them, the following are included in the step S5:

[0067] S51: Provide a clear fingerprint collection guidance program to ensure that users place their fingers correctly;

[0068] S52: Provide a real-time feedback function during the collection process to help users adjust the position of their fingers;

[0069] S53: Set up a real-time monitoring function for user feedback to ensure that problems can be detected and processed in a timely manner to improve the user experience.

[0070] Among them, the following are included in the step S6:

[0071] S61: Optimize the collaborative work of hardware and software at set intervals, reduce power consumption, and extend the battery life of the device;

[0072] S62: Regularly test the performance of the system and perform self-checks. When problems are detected during self-checks, repair the problems in a timely manner.

[0073] Among them, the following are included in the step S7:

[0074] S71: Install a firewall to protect fingerprint recognition technology and encrypt the storage of fingerprint data to prevent fingerprint data from being stolen;

[0075] S72: Combine the introduction of technologies such as liveness detection to prevent forged fingerprint attacks.

[0076] Specifically, when using the present invention, the quality of the fingerprint recognition sensor is improved by using a sensor with a higher resolution to enhance the accuracy of capturing fingerprint details, and by selecting sensor materials with high wear resistance and anti-pollution properties to extend the service life. The multi-spectral imaging technology is adopted to enhance the adaptability to various environments. Image preprocessing is carried out to improve the image quality by techniques such as filtering and contrast adjustment, reduce noise interference, ensure the clarity of fingerprint features, and perform post-repair on blurred or incomplete fingerprint images to repair damaged or blurred areas and improve the recognition effect. By combining detailed features and global features, the recognition accuracy is improved. Deep learning techniques such as convolutional neural networks are used to set the function of automatically extracting effective features, introduce multi-modal matching, make comprehensive judgments by combining multiple features, and add a live detection function to prevent the appearance of forged fingerprints. The algorithms of graph matching or local feature matching are used to improve the matching speed and accuracy, and the matching threshold is dynamically adjusted according to the environment to reduce false recognition and rejection. By combining fingerprints with other biometric features, the overall performance of the system is enhanced, and algorithms adapted to different environments are designed to ensure the stable operation of the system under various conditions. The system is decomposed into multiple independent modules to isolate faults and reduce the impact on other parts of the system. A mechanism capable of detecting and handling errors is designed to improve the fault tolerance rate. A clear fingerprint collection guidance program is provided to ensure that users place their fingers correctly, and a real-time feedback function is provided during the collection process to help users adjust the finger position. A real-time monitoring function is set for user feedback to ensure that problems can be detected and handled in a timely manner, thereby enhancing the user experience. The collaborative work of hardware and software is optimized at regular intervals to reduce power consumption and extend the battery life of the device. The performance of the system is tested regularly, and self-checking is carried out. When problems are detected during self-checking, the problems are repaired in a timely manner. A firewall protection is installed for the fingerprint recognition technology, and the fingerprint data is encrypted for storage to prevent the fingerprint data from being stolen. The introduction of technologies such as live detection is combined to prevent forged fingerprint attacks.

[0077] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made in these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fingerprint recognition control method, characterized in that, It includes the following: S1: Conduct hardware optimization and optimize sensor technology; S2: Perform preprocessing on images; S3: Optimize feature extraction algorithms and simultaneously improve and optimize matching algorithms; S4: Enhance system robustness and improve data quality and diversity; S5: Improve user interaction and feedback capabilities; S6: Regularly conduct system integration and optimization, and simultaneously regularly conduct testing work; S7: Improve security firewalls and privacy protection, and can cooperate with multimodal fusion.

2. The fingerprint recognition control method according to claim 1, wherein: The following is included in step S1: S11: Improve the quality of fingerprint recognition sensors, use sensors with higher resolution, and improve the accuracy of capturing fingerprint details; S12: Select sensor materials with high wear resistance and anti-pollution to increase the service life; S13: Adopt multispectral imaging technology to enhance multi-environment adaptability.

3. A fingerprint recognition control method according to claim 1, characterized in that: The following is included in step S2: S21: Perform preprocessing on images, and improve image quality through techniques such as filtering and contrast adjustment; S22: Reduce noise interference to ensure the clarity of fingerprint features; S23: Repair blurred or incomplete fingerprint images in the later stage, repair damaged or blurred areas, and improve the recognition effect.

4. A fingerprint recognition control method according to claim 1, characterized in that: The following is included in step S3: S31: Combine local features and global features to improve recognition accuracy, and use deep learning technologies such as convolutional neural networks to set the function of automatically extracting effective features; S32: Introduce multimodal matching, combine multiple features for comprehensive judgment, and add a live detection function to prevent the appearance of forged fingerprints; S33: Cooperate with algorithms such as graph matching or local feature matching to improve the matching speed and accuracy, and dynamically adjust the matching threshold according to the environment to reduce false recognition and rejection.

5. A fingerprint recognition control method according to claim 1, characterized in that: The following is included in step S4: S41: Combine fingerprints with other biometric features to improve the overall performance of the system, and design algorithms suitable for different environments to ensure the stable operation of the system under various conditions; S42: Decompose the system into multiple independent modules to isolate faults and reduce the impact on other parts of the system; S43: Design a mechanism that can detect and handle errors to improve the fault tolerance rate.

6. A fingerprint recognition control method according to claim 1, characterized in that: The following is included in step S5: S51: Provide a clear fingerprint collection guidance program to ensure that users place their fingers correctly; S52: Provide a real-time feedback function during the collection process to help users adjust the position of their fingers; S53: Set a real-time monitoring function for user feedback to ensure that problems can be detected and processed in a timely manner, thereby improving the user experience.

7. A fingerprint recognition control method according to claim 1, characterized in that: The following is included in step S6: S61: Set a periodic optimization for the coordinated work of hardware and software, reduce power consumption, and extend the battery life of the device; S62: Regularly test the performance of the system and conduct self-checking work. When problems are detected during self-checking, repair the problems in a timely manner.

8. A fingerprint recognition control method according to claim 1, wherein: The following is included in step S7: S71: Install a firewall protection for fingerprint recognition technology and encrypt and store fingerprint data to prevent fingerprint data from being stolen; S72: In cooperation with technologies such as live detection, prevent forged fingerprint attacks.

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