Vehicle safety control system based on multi-mode biological feature recognition technology

Abstract

The invention discloses a vehicle safety control system based on a multi-mode biological feature recognition technology. The vehicle safety control system comprises an approach detection module, an identity information acquisition module, a feature extraction module, a data processing and analysis module and a safety control module, according to the vehicle safety control system based on the multi-mode biological feature recognition technology, the biological feature recognition technology and vehicle intelligent control are combined according to the core technical scheme, and the technical level of traditional vehicle identity verification and safety protection is remarkably improved; according to the system, the efficient and accurate identity verification function is achieved by fusing various biological feature data such as fingerprints, irises and faces and combining an advanced feature extraction algorithm and a deep learning model, meanwhile, a predictive triggering mechanism is introduced in the system, the safety verification process is automatically started when a driver approaches a vehicle, manual operation is not needed, and the safety verification efficiency is improved. Not only is convenience of user experience improved, but also active identification and protection measures can be taken before potential threats occur.

Description

Technical Field

[0001] The present invention relates to the technical fields of intelligent transportation systems and automotive electronics technology, and specifically to a vehicle safety control system based on multimodal biometric recognition technology. Background Art

[0002] Vehicle safety control systems are an important part of modern automotive electronics technology. They integrate a variety of safety technologies aimed at improving vehicle safety and protecting passengers and vehicles from damage. These systems typically include functions such as biometric recognition, intelligent monitoring, collision warning, automatic emergency braking, lane keeping assist, and blind spot monitoring. By integrating these advanced technologies, vehicle safety control systems can monitor the vehicle status, driver behavior, and surrounding environment in real time, and thus take timely measures before potential dangers occur to ensure driving safety.

[0003] Existing vehicle safety control systems have the following defects: First, the problem of recognition accuracy: Biometric recognition is not absolutely accurate when verifying identities. From the perspective of biometric storage, what is saved is not the original high-definition information, but the measured values of some deterministic features. For example, fingerprints are processed into points marking valley lines, ridge lines, and turns, which greatly reduces their uniqueness. In actual use, to avoid false alarms, readers and verifiers will reduce the accuracy, resulting in possible matching repetitions of biometric features of different individuals and affecting the reliability of identity verification; Second, the limited scope of application: Not everyone can apply biometric recognition. When operating a large biometric recognition system, some people may have special physical conditions and rapid changes in biometric attributes, resulting in the inability to match the entered fingerprints all the time, and other verification methods have to be adopted, which limits the comprehensive application of biometric recognition technology; Third, it is easy to be copied and deceived: Biometric recognition data is very easy to be copied, and there are risks of being captured, copied, and reused for information such as fingerprints, faces, irises, and retinas. Biometric recognition systems are also very easy to be deceived. By some simple means, such as making fake fingerprints with plasticine and using fingerprint oil prints, the recognition system can be bypassed, and the security is difficult to guarantee; Fourth, the risk of data leakage: Intelligent vehicles collect a large amount of sensitive data containing biometric information. Once this data is leaked, it will violate user privacy and may also be used for malicious attacks. In intelligent transportation systems, there are also risks in the collection, storage, use, and transfer of biometric recognition data. For example, face recognition devices in hotels and sales centers may lead to problems such as the trafficking of citizens' information data; Fifth, the hidden danger of privacy infringement: The biometric information of users collected by intelligent vehicles through in-vehicle sensors may break the "private domain" of personal privacy during the process of data open sharing, resulting in privacy infringement. Moreover, in the process of using biometric recognition data, personal information flows and spreads between collectors and users, and the Internet era makes privacy infringement more concealed and has a greater impact. Summary of the Invention

[0004] The object of the present invention is to provide a vehicle safety control system based on multimodal biometric recognition technology to solve the problems raised in the above-mentioned background art.

[0005] To achieve the above object, the present invention provides the following technical solution: A vehicle safety control system based on multimodal biometric recognition technology, including a proximity detection module, which is controlled and connected to an identity information acquisition module, the identity information acquisition module is data-connected to a feature extraction module, the feature extraction module is data-connected to a data processing and analysis module, the data processing and analysis module is controlled and connected to a safety control module, and the feature extraction module includes a preprocessing module, a data integration module, a fingerprint recognition module, an iris feature recognition module, a feature vector encoding module, and a data compression module.

[0006] As a further technical solution of the present invention, the proximity detection module includes a radar sensor module and an infrared sensor module.

[0007] As a further technical solution of the present invention, the identity information acquisition module includes a fingerprint acquisition module and an iris image acquisition module.

[0008] As a further technical solution of the present invention, the preprocessing module includes an image denoising module and an image enhancement module.

[0009] As a further technical solution of the present invention, the data integration module includes a data synchronization module and a data verification module.

[0010] As a further technical solution of the present invention, the data processing and analysis module includes a feature template storage module, a backup and recovery module, a template matching module, a deep learning verification module, a multimodal fusion module, and an auxiliary verification module.

[0011] As a further technical solution of the present invention, the safety control module includes a door unlocking module, an engine ignition module, an alarm module, and a remote notification and monitoring module.

[0012] As a further technical solution of the present invention, the safety control module is controlled and connected to a modular expansion support module, and the modular expansion support module is controlled and connected to the proximity detection module, the identity information acquisition module, the feature extraction module, and the data processing and analysis module. The modular expansion support module includes a hardware interface management module, a software management module, a human-computer interaction module, and a configuration data storage module.

[0013] As a further technical solution of the present invention, the hardware interface management module includes a sensor interface module and an actuator interface module.

[0014] As a further technical solution of the present invention, the software management module includes a loading module and an unloading module.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention proposes a vehicle safety control system based on multi-modal biometric recognition technology. Its core technical solution combines biometric recognition technology with vehicle intelligent control, significantly improving the technical level of traditional vehicle identity verification and safety protection. The system realizes efficient and accurate identity verification functions by integrating multiple biometric data such as fingerprints, irises, and faces, and combining advanced feature extraction algorithms and deep learning models. At the same time, the system introduces a predictive trigger mechanism, which automatically starts the security verification process when the driver approaches the vehicle without manual operation, not only improving the convenience of the user experience, but also being able to actively identify and take protective measures before potential threats occur. In addition, the present invention constructs a multi-level security verification system, combining biometric recognition technology with means such as environmental information detection and real-time data analysis, effectively preventing the occurrence of spoofing attacks and illegal intrusion behaviors, and further enhancing the security of the system. In terms of intelligent control, the system provides real-time driving assistance functions by dynamically monitoring the driver's state and the vehicle's operating environment, significantly improving driving safety and comfort, and adopts a modular design and extensible architecture, supporting highly flexible customized configurations, and providing an important basis for the integration of future intelligent driving and vehicle networking technologies. The hardware design of the system also takes into account high reliability and durability, and can still operate stably under complex environmental conditions. Generally speaking, the present invention not only solves the deficiencies of the prior art in terms of security, intelligent level, and adaptability, but also meets the core requirements of vehicle identity verification and safety protection in the new era. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0017] Figure 2 It is a module architecture diagram of the feature extraction module of the present invention;

[0018] Figure 3 It is a module architecture diagram of the data processing and analysis module of the present invention;

[0019] Figure 4 It is a module architecture diagram of the preprocessing module of the present invention;

[0020] Figure 5 It is a module architecture diagram of the image enhancement module of the present invention;

[0021] Figure 6 It is a module architecture diagram of the hardware interface management module of the present invention;

[0022] Figure 7It is the module architecture diagram of the software management module of the present invention;

[0023] Figure 8 It is the system flow chart of the present invention;

[0024] Figure 9 It is the installation application schematic diagram of the present invention;

[0025] Figure 10 It is the application flow chart of the present invention.

[0026] In the figure: 1. Proximity detection module; 11. Radar sensor module; 12. Infrared sensor module; 2. Identity information acquisition module; 21. Fingerprint acquisition module; 22. Iris image acquisition module; 3. Feature extraction module; 31. Preprocessing module; 311. Image denoising module; 312. Image enhancement module; 32. Data integration module; 321. Data synchronization module; 322. Data verification module; 33. Fingerprint recognition module; 34. Iris feature recognition module; 35. Feature vector encoding module; 36. Data compression module; 4. Data processing and analysis module; 41. Feature template storage module; 42. Backup and recovery module; 43. Template matching module; 44. Deep learning verification module; 45. Multimodal fusion module; 46. Auxiliary verification module; 5. Security control module; 51. Door unlocking module; 52. Engine ignition module; 53. Alarm module; 54. Remote notification and monitoring module; 6. Modular expansion support module; 61. Hardware interface management module; 611. Sensor interface module; 612. Actuator interface module; 62. Software management module; 621. Loading module; 622. Unloading module; 63. Human-computer interaction module; 64. Configuration data storage module. Specific implementation manners

[0027] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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 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.

[0028] Please refer to the attached Figure 1 - attached Figure 10, an embodiment provided by the present invention: A vehicle safety control system based on multi-modal biometric recognition technology, including a proximity detection module 1, which is controllably connected to an identity information acquisition module 2, the identity information acquisition module 2 is data-connected to a feature extraction module 3, the feature extraction module 3 is data-connected to a data processing and analysis module 4, the data processing and analysis module 4 is controllably connected to a safety control module 5. The feature extraction module 3 includes a preprocessing module 31, a data integration module 32, a fingerprint recognition module 33, an iris feature recognition module 34, a feature vector encoding module 35 and a data compression module 36; the proximity detection module 1 includes a radar sensor module 11 and an infrared sensor module 12. The radar sensor module 11 detects the approach of the driver through radar waves, and the infrared sensor module 12 detects the heat radiation of the driver through infrared rays to detect the approach of the driver; the identity information acquisition module 2 includes a fingerprint acquisition module 21 and an iris image acquisition module 22; the preprocessing module 31 includes an image denoising module 311 and an image enhancement module 312. The image denoising module 311 is used to remove noise in the image and improve the image quality, and the image enhancement module 312 is used to enhance the image contrast to make the features more obvious; the data integration module 32 includes a data synchronization module 321 and a data verification module 322. The data synchronization module 321 is used to ensure the time synchronization of the data of each sensor, and the data verification module 322 is used to perform a preliminary verification on the collected data to remove outliers; the data processing and analysis module 4 includes a feature template storage module 41, a backup and recovery module 42, a template matching module 43, a deep learning verification module 44, a multi-modal fusion module 45 and an auxiliary verification module 46. The feature template storage module 41 pre-stores the biometric data templates of authorized drivers and completes the entry during the initial setting of the vehicle. The backup and recovery module 42 is used to ensure the security and recoverability of the data. The template matching module 43 matches the extracted features with the templates. The deep learning verification module 44 uses deep learning technology for identity verification. The multi-modal fusion module 45 is used to combine the recognition results of multiple biometrics to improve the accuracy of identity verification. The auxiliary verification module 46 is used to select other modalities for auxiliary verification when the single-modal recognition fails; the safety control module 5 includes a door unlocking module 51, an engine ignition module 52, an alarm module 53 and a remote notification and monitoring module 54. The door unlocking module 51 is used to control the unlocking of the door, the engine ignition module 52 is used to control the engine ignition. The alarm module 53 is triggered to issue an alarm when the identity verification fails, and sends a notification to the owner's mobile device or contacts the monitoring center through the remote notification and monitoring module 54 to ensure the safety of the vehicle;The modular expansion support module 6 is controlled and connected to the safety control module 5, and the modular expansion support module 6 is controlled and connected to the proximity detection module 1, the identity information acquisition module 2, the feature extraction module 3, and the data processing and analysis module 4. The modular expansion support module 6 includes a hardware interface management module 61, a software management module 62, a human-computer interaction module 63, and a configuration data storage module 64. The human-computer interaction module 63 is used for human-computer interaction and displays configuration options and the current configuration status. The configuration data storage module 64 is used to store the user's customized configuration. The hardware interface management module 61 includes a sensor interface module 611 and an actuator interface module 612. The sensor interface module 611 is used to provide an interface for sensor access, and the actuator interface module 612 is used to provide an interface for actuator access. The software management module 62 includes a loading module 621 and an unloading module 622. The loading module 621 is used to load the modules required by the system, and the unloading module 622 is used to unload the modules that are no longer needed.

[0029] Working principle: The present invention proposes a vehicle safety control system based on multi-modal biometric recognition technology. This system effectively integrates modern biometric recognition technology into the vehicle's security startup mechanism, aiming to significantly improve vehicle anti-theft performance and user experience. The overall architecture of the system includes multiple key components: proximity detection module 1, identity information acquisition module 2, feature extraction module 3, data processing and analysis module 4, and security control module 5. These modules cooperate with each other to achieve intelligent identity verification and precise control of vehicle functions. In terms of physical form, this system is designed to be compact and highly integrated. The main hardware components can be embedded in key positions inside the vehicle through the modular expansion support module 6. Among them, the sensor interface module 611 in the hardware interface management module 61 is used to provide an interface for sensor access, and the actuator interface module 612 is used to provide an interface for actuator access. The loading module 621 in the software management module 62 is used to load the modules required by the system, and the unloading module 622 is used to unload the modules that are no longer needed. The human-machine interaction module 63 is used for human-machine interaction and displays configuration options and the current configuration status. The configuration data storage module 64 is used to store the customized configurations of users. The fingerprint acquisition module 21 is installed near the door handle so that fingerprint data can be acquired when the driver touches it naturally. The iris image acquisition module 22 is built into the interior rearview mirror or other prominent positions that do not affect the driving vision to ensure that iris images can be captured without additional operations. This design not only ensures the effectiveness and reliability of the hardware components but also maintains the cleanliness and functionality of the interior space of the vehicle. When using the present invention for vehicle safety control, first, when the driver approaches the vehicle, the radar sensor module 11 in the proximity detection module 1 detects the driver's approach through radar waves, and the infrared sensor module 12 detects the driver's heat radiation through infrared rays. After detecting the driver's approach, it triggers the acquisition of identity information. The fingerprint acquisition module 21 and the iris image acquisition module 22 are automatically activated to start the fingerprint scanner and iris camera for identity information acquisition, and start to collect the driver's fingerprint images or iris patterns in real time. The collected biometric data is transmitted to the feature extraction module 3. The preprocessing module 31 preprocesses the collected biometric data to improve the accuracy of subsequent processing. The image denoising module 311 is used to remove noise in the image and improve the image quality. The image enhancement module 312 is used to enhance the image contrast to make the features more obvious, and the data integration module 32 integrates data from different sensors to ensure the synchronization and accuracy of data acquisition. The data synchronization module 321 is used to ensure the time synchronization of data from each sensor, and the data verification module 322 is used to preliminarily verify the collected data and remove outliers. Then, the fingerprint recognition module 33 and the iris feature recognition module 34 identify and extract fingerprint features and iris features, the feature vector encoding module 35 converts the biometric features into digital feature vectors that can be used for identity verification, and the data compression module 36 compresses the feature vectors.Reduce the storage space, and then process and analyze the feature data through the data processing and analysis module 4. The feature template storage module 41 has pre-stored the biometric data templates of authorized drivers and completed the input during the initial vehicle setup. The backup and recovery module 42 is used to ensure the security and recoverability of the data. The template matching module 43 matches the extracted features with the templates. The deep learning verification module 44 uses deep learning technology for identity verification. The multi-modal fusion module 45 is used to combine the recognition results of multiple biometrics to improve the accuracy of identity verification. The auxiliary verification module 46 is used to select other modalities for auxiliary verification when single-modal recognition fails. Once the verification result is a successful match, the door unlocking module 51 in the security control module 5 immediately unlocks the door, and the engine ignition module 52 controls the engine ignition. On the contrary, if the identity verification fails, the alarm module 53 is triggered to issue an alarm, and a notification is sent to the owner's mobile device through the remote notification monitoring module 54 or contact the monitoring center to ensure the security of the vehicle. The security mechanism of the present invention combines a multi-factor authentication strategy, which can improve the protection level of the system, effectively prevent potential illegal intrusion means such as fingerprint film deception and iris photo attacks, and ensure that the driver can conveniently operate and understand the system functions during use. Considering that different drivers may have multiple biometric data, the system supports multi-modal recognition technology, which means that even if a misjudgment occurs in a certain biometric recognition, the information of other modalities can assist in confirming the identity, further improving the overall accuracy and reliability of the system.

[0030] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A vehicle safety control system based on multimodal biometric recognition technology, including a proximity detection module (1), characterized in that: A proximity detection module (1) is controllably connected to an identity information acquisition module (2). The identity information acquisition module (2) is data-connected to a feature extraction module (3). The feature extraction module (3) is data-connected to a data processing and analysis module (4). The data processing and analysis module (4) is controllably connected to a security control module (5). The feature extraction module (3) includes a preprocessing module (31), a data integration module (32), a fingerprint recognition module (33), an iris feature recognition module (34), a feature vector encoding module (35), and a data compression module (36).

2. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, wherein: The proximity detection module (1) includes a radar sensor module (11) and an infrared sensor module (12).

3. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, characterized in that: The identity information acquisition module (2) includes a fingerprint acquisition module (21) and an iris image acquisition module (22).

4. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, characterized in that: The preprocessing module (31) includes an image denoising module (311) and an image enhancement module (312).

5. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, characterized in that: The data integration module (32) includes a data synchronization module (321) and a data verification module (322).

6. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, characterized in that: The data processing and analysis module (4) includes a feature template storage module (41), a backup and recovery module (42), a template matching module (43), a deep learning verification module (44), a multi-modal fusion module (45), and an auxiliary verification module (46).

7. The vehicle safety control system based on multimodal biometric recognition technology according to claim 1, wherein: The security control module (5) includes a door unlocking module (51), an engine ignition module (52), an alarm module (53), and a remote notification and monitoring module (54).

8. The vehicle safety control system based on multi-modal biometric recognition technology according to claim 7, characterized in that: The security control module (5) is controllably connected to a modular expansion support module (6), and the modular expansion support module (6) is controllably connected to the proximity detection module (1), the identity information acquisition module (2), the feature extraction module (3), and the data processing and analysis module (4). The modular expansion support module (6) includes a hardware interface management module (61), a software management module (62), a human-machine interaction module (63), and a configuration data storage module (64).

9. The vehicle safety control system based on multimodal biometric recognition technology according to claim 8, characterized in that: The hardware interface management module (61) includes a sensor interface module (611) and an actuator interface module (612).

10. The vehicle safety control system based on multimodal biometric recognition technology according to claim 8, characterized in that: The software management module (62) includes a loading module (621) and an unloading module (622).

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