A Dual-Mode Biometric Fusion Security Authentication System and Method Based on Magnetic Coupling

Abstract

This invention discloses a dual-mode biometric fusion security authentication system and method based on magnetic coupling, relating to the fields of biometric recognition and information security technology. The system includes the following steps: when the magnetic interface enters the connection range and establishes a connection, a Hall element outputs a magnetic field change signal. The main controller combines this signal with the recognition control signal to complete the connection determination and supplies power to the fingerprint acquisition device and image acquisition device via the magnetic interface. Simultaneously, it completes the data interface configuration of the auxiliary processor. This invention improves the reliability of identity authentication and reduces the risk of false positives by fusing fingerprint and face recognition with liveness detection and dynamic tokens. It also achieves rapid connection and automatic recognition via the magnetic interface, completing status detection and power supply control during the access process, simplifying the operation process and supporting convenient disassembly and maintenance, thereby improving efficiency and enhancing adaptability to multiple scenarios.

Description

Technical Field

[0001] This invention relates to the field of biometric recognition and information security technology, specifically to a dual-mode biometric fusion security authentication system and method based on magnetic coupling. Background Technology

[0002] With the continuous development of smart terminal devices and security authentication needs, biometric identification methods have gradually become the mainstream technology. Among them, fingerprint recognition and facial recognition are the two most widely used biometric identification methods, and have been widely applied in scenarios such as access control, mobile terminal unlocking, and financial payments. Traditional systems typically use separate fingerprint acquisition devices and image acquisition devices to obtain the user's fingerprint information and facial image information respectively, and complete the identity determination through their respective recognition processes. Building on this, some systems have begun to explore the combined use of multiple biometric features to improve the security level and anti-forgery capabilities of identity authentication, thus gradually moving towards multimodal fusion authentication.

[0003] However, in existing technologies, fingerprint acquisition devices and camera devices are often designed separately, resulting in a complex overall system structure. This not only increases the size and weight of the device but also introduces higher costs during production and assembly. Furthermore, in practical applications, fingerprint recognition performance is easily affected by dirt and surface wear, while facial recognition performance is susceptible to interference from changes in lighting and sampling angle deviations, thus reducing overall recognition accuracy. In addition, traditional systems typically rely on tools for disassembly and assembly during module maintenance and replacement, making the process cumbersome and failing to meet the needs for rapid maintenance and convenient use. Therefore, they still have significant shortcomings in terms of structural integration, recognition stability, and ease of maintenance.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a dual-mode biometric fusion security authentication system and method based on magnetic coupling to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a dual-mode biometric fusion security authentication method based on magnetic coupling, comprising the following steps: When the magnetic interface enters the connection range and establishes a connection, the Hall element outputs a magnetic field change signal. The main controller combines the recognition control signal to complete the connection determination and supplies power to the fingerprint acquisition device and image acquisition device through the magnetic interface. At the same time, it completes the data interface configuration of the auxiliary processor. After completing the connection determination and interface configuration, the main controller sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. Based on the acquired fingerprint and face image data, the main controller calls the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint and face features. Based on valid fingerprint features and facial features, the security chip matches and compares them with pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. Combining the authentication result with the dynamic token, the security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process.

[0007] Preferably, the steps to refine the magnetic connection status recognition process and improve the stability and accuracy of connection determination are as follows: As the magnetic interface enters the sensing range, the Hall element continuously outputs a magnetic field change signal and records the duration of the signal change; The main controller continuously samples the magnetic field change signal and judges the stability of the sampling results; When the sampling signal remains consistent within a set time range, connection confirmation is completed in conjunction with the identification control signal. When the connection confirmation result is successful, the power supply control and data interface configuration process is triggered to complete the stable connection determination.

[0008] Preferably, the steps to standardize the acquisition process of fingerprint and facial images and improve data collection consistency are as follows: After the main controller sends out the acquisition control information, the auxiliary processor establishes a communication path with the universal serial bus; Fingerprint image data and face image data are received separately through the communication path; Perform integrity checks on the received data and mark any abnormal data. The verified image data is transmitted to the main controller to form standardized input data.

[0009] Preferably, the steps to enhance the reliability of the liveness detection process and improve the quality of biometric recognition are as follows: Gray-scale distribution analysis was performed on the fingerprint image, and texture detail information was extracted; Perform multi-frame continuous analysis on facial images to extract dynamic change information; Input texture detail information and dynamic change information into the liveness detection process separately; Based on the detection results, valid fingerprint and facial features are selected for subsequent comparison processing.

[0010] Preferably, a partitioned gradient sequence is formed for the grayscale distribution and continuous texture changes are extracted. A time change trajectory is established for multiple frames of images and stable dynamic features are extracted. The two types of features are synchronously aligned and a consistency judgment is performed. Only features that simultaneously meet the requirements of texture continuity and dynamic response are retained for comparison processing.

[0011] The preferred steps to standardize the feature comparison process and improve the consistency of authentication results are as follows: The extracted fingerprint and facial features are formatted and organized. Each matching calculation is performed with a pre-stored template to obtain the corresponding matching result; Threshold determination is applied to the matching results to determine their respective recognition status; When both fingerprint recognition and facial recognition status meet the requirements, a unified authentication result is output.

[0012] Preferably, the steps to strengthen the security protection of authentication results and improve the security of data transmission are as follows: After the authentication result is generated, the result data is combined with the dynamic token to form the data to be processed; The security chip performs encryption processing on the data to be processed; The encrypted data is marked with an integrity verification tag; The processed data is then transmitted to an external device via an auxiliary processor.

[0013] Preferably, after the result data and dynamic token are combined to form the data to be processed, the security chip performs encryption operations on the data to be processed and generates verification information simultaneously; the encryption result and verification information are bound together to form associated data; the associated data is verified for consistency during transmission; and the data is output to an external device via an auxiliary processor if the verification passes.

[0014] Preferably, the steps to improve the connection status verification mechanism during the authentication process and enhance system stability are as follows: Continuously receive magnetic connection status signals during data transmission; Real-time monitoring of changes in connection status signals; When an abnormal change in connection status is detected, the abnormal information is recorded and the current data transmission is interrupted; Once the connection status stabilizes, the authentication process is restarted, thus completing the closed loop of status verification.

[0015] A dual-mode biometric fusion security authentication system based on magnetic coupling includes a magnetic attraction detection module, a data acquisition and processing module, a liveness feature extraction module, a feature matching authentication module, and an encrypted transmission verification module. The magnetic attraction detection module, when the magnetic attraction interface enters the connection range and establishes a connection, outputs a magnetic field change signal with the help of the Hall element. The main controller combines the recognition control signal to complete the connection determination, and supplies power to the fingerprint acquisition device and the image acquisition device through the magnetic attraction interface. At the same time, it completes the data interface configuration of the auxiliary processor. The data acquisition and processing module, after completing connection determination and interface configuration, sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. The liveness feature extraction module, based on the acquired fingerprint image data and face image data, uses the main controller to call the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint features and face features; The feature matching and authentication module compares the valid fingerprint features and facial features with the pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. The encrypted transmission verification module combines the authentication result with the dynamic token. The security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention enhances the reliability of identity verification by integrating fingerprint and facial recognition within the same authentication process, combined with liveness detection and dynamic token mechanisms. The simultaneous collection and comparison of both biometric features effectively reduces the risk of misjudgment from a single identification method. Furthermore, the liveness detection step verifies the authenticity of the input source, making the authentication results more reliable and stable, thereby improving the overall security level.

[0017] This invention utilizes a magnetic interface for rapid connection and automatic identification, simultaneously performing status detection and power supply control during device connection, ensuring a smoother system startup. Through a unified data transmission path and interface design, it reduces operational complexity during connection and supports convenient disassembly and maintenance in subsequent use, thereby improving device efficiency, reducing maintenance costs, and enhancing adaptability in various scenarios. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a schematic diagram of the magnetic interface structure of the present invention.

[0020] Figure 2 This is a schematic diagram of the magnetic attraction contact and elastic structure of the present invention.

[0021] Figure 3 This is a schematic diagram of the power supply regulator circuit of the present invention.

[0022] Figure 4 This is a schematic diagram of the overall system architecture and data interaction process of the present invention.

[0023] Figure 5 This is a schematic diagram of the peripheral circuit connection of the main control chip of the present invention.

[0024] Figure 6 This is a schematic diagram of the auxiliary processing chip and peripheral interface circuit of the present invention.

[0025] Figure 7 This is a schematic diagram of the security chip interaction and authentication process of the present invention. Detailed Implementation

[0026] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0027] This invention provides, for example Figure 1-7 The dual-mode biometric fusion security authentication method based on magnetic coupling shown includes the following steps: When the magnetic interface enters the connection range and establishes a connection, the Hall element outputs a magnetic field change signal. The main controller combines the recognition control signal to complete the connection determination and supplies power to the fingerprint acquisition device and image acquisition device through the magnetic interface. At the same time, it completes the data interface configuration of the auxiliary processor. After completing the connection determination and interface configuration, the main controller sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. Based on the acquired fingerprint and face image data, the main controller calls the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint and face features. Based on valid fingerprint features and facial features, the security chip matches and compares them with pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. Combining the authentication result with the dynamic token, the security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process. The dual-mode biometric fusion security authentication scheme based on magnetic coupling involved in this invention is designed in an integrated manner at the hardware level around five core elements: control coordination, data processing, feature acquisition, security protection, and physical connection. Through the coordinated cooperation of multiple devices, it achieves stable data acquisition, efficient information processing, and secure and reliable authentication output.

[0028] Firstly, in terms of control and scheduling, a main control chip is set as the core processing unit for overall operation. This main control chip is a 32-bit microcontroller based on the Arm Cortex-M4 core, typically the HC32F460, which operates at 3.3 volts. This chip possesses high computing power and peripheral interface resources, capable of handling functions such as status determination, process scheduling, data aggregation, and peripheral control. During actual operation, the main control chip is responsible for receiving various signals from the magnetic attraction detection, power management, and data processing sides, and performing comprehensive judgments based on preset logic to uniformly schedule all functional components.

[0029] Secondly, in terms of data sharing and communication coordination, a slave chip is introduced as an auxiliary processing unit. This slave chip is based on the Arm Cortex-M33 core, operates at a frequency of up to 180 MHz, and also operates at 3.3 volts. By transferring some data acquisition and transmission tasks from the main control chip to the slave chip, the computational burden on the main control chip can be effectively reduced, improving overall operating efficiency. The slave chip and the main control chip maintain data interaction through serial communication, undertaking functions such as data relay, interface adaptation, and peripheral access during execution, making data flow smoother.

[0030] Furthermore, regarding peripheral connectivity, the slave chip achieves unified access to both the fingerprint and image acquisition devices by connecting to a universal serial bus (USB) control chip. The preferred USB control chip is the CH334, which features multi-interface integration capabilities and can simultaneously support multiple peripheral connection requirements. In practical applications, both the fingerprint and image acquisition devices are connected through this control chip, thus achieving unified management of the data acquisition path. This approach reduces wiring complexity caused by dispersed interfaces and improves data transmission stability.

[0031] For connection status detection, a Hall effect sensor is configured to identify the magnetic connection. The preferred sensor is the A3144 model, which has high sensitivity to changes in magnetic fields. When the integrated acquisition unit approaches the magnetic interface on the device, the magnetic field distribution changes. The Hall effect sensor converts this change into a voltage level signal and outputs it to the main control chip. Upon receiving this signal, the main control chip combines it with the identification control signal to determine the status and confirm the validity of the connection. This detection method features fast response and high stability, providing a reliable foundation for subsequent power supply and data communication.

[0032] In terms of security, a dedicated security chip is used to handle data encryption and authentication. This security chip, the LCSHA204, meets EAL4+ security standards and integrates multiple security detection mechanisms and tamper-proof designs. During operation, this chip handles sensitive data processing tasks, including feature data encryption, authentication result generation, and dynamic token generation. By introducing this type of security chip, the system's resistance to attacks during data transmission and storage is effectively enhanced, preventing data from being illegally tampered with or stolen.

[0033] For biometric data acquisition, fingerprint recognition and image acquisition devices are configured separately. The fingerprint recognition device acquires the user's fingerprint image and performs preliminary feature extraction; the image acquisition device acquires facial image information, providing basic data for subsequent recognition. Both types of acquisition devices are connected to a slave chip via a universal serial bus control chip, thus achieving a unified data input path. During collaborative operation, both types of biometric data can be acquired simultaneously, improving the synchronization of the authentication process.

[0034] For physical connectivity, a magnetic interface is used as the electrical connection and data transmission carrier. This interface is based on a PogoPin contact design and has a six-pin layout, including a positive power terminal, a ground power terminal, a negative data terminal, a positive data terminal, an identification control terminal, and a magnetic detection terminal. The identification control terminal transmits device identification information, while the magnetic detection terminal provides feedback on the connection status signal. This six-pin design allows for the integration of power supply, data communication, and status detection within a limited space.

[0035] In terms of interface structure design, the pins adopt a double-row trapezoidal arrangement with a spacing of 2.54 mm. This arrangement has reverse connection protection characteristics, effectively avoiding electrical risks caused by incorrect connection direction. Regarding material selection, the metal probes are made of beryllium copper, which has good conductivity and elasticity; the spring is made of stainless steel to ensure rebound performance during long-term use; the shell is made of polybutylene terephthalate, which has high mechanical strength and heat resistance; and the magnetic attraction part is made of neodymium iron boron and symmetrically embedded on both sides of the interface shell to provide stable attraction force.

[0036] Through the coordinated configuration of the above-mentioned parts, the present invention achieves the organic integration of control coordination, data acquisition, information processing, security protection and connection management at the hardware level, which not only improves the overall integration, but also achieves good engineering implementation results in terms of stability, security and ease of maintenance.

[0037] Magnetic connection detection and power activation serve as the starting point of the entire authentication process. The core of this process is to complete connection identification and system wake-up through physical proximity triggering, electrical status confirmation, and logical judgment, thereby providing a stable operating foundation for subsequent data collection and authentication processing.

[0038] As the integrated acquisition component approaches the magnetic connection point of the external device, a stable magnetic field distribution is formed between the magnetic element embedded in the device and the magnetic connector at the interface. During this process, the Hall sensor continuously monitors the changes in the magnetic field in real time. Once the magnetic field strength reaches a preset trigger threshold, the Hall sensor immediately converts the magnetic field change into a corresponding level signal output. In the magnetically engaged state, it outputs a low-level signal (MAG_DET is low), while in the disengaged state, it outputs a high-level signal (MAG_DET is high). This level change provides a clear criterion for physical connection.

[0039] After receiving the level signal from the Hall sensor, the main control chip first identifies the current state based on its internally set judgment rules. During this identification process, it not only performs single-point judgment on the level state but also comprehensively analyzes the duration and stability of the signal change process to avoid misjudgments caused by transient interference or false triggering. Once the magnetic connection is confirmed to be stably established, the main control chip further performs dual verification using the identification control signal. By judging the logical consistency between the magnetic detection signal and the identification control signal, reliable confirmation of the connection status is achieved.

[0040] After the connection is confirmed, the main control chip enters the power activation phase. Power is supplied to the fingerprint and image acquisition devices via the positive and ground pins in the magnetic interface, while simultaneously initializing the data transmission interface of the auxiliary processor. During this process, the main control chip concurrently pre-configures the data communication path, including initializing the positive and negative data pins and setting the communication direction, establishing the foundation for subsequent image data transmission.

[0041] In the power supply stage, a dedicated voltage regulator circuit is used to adjust the input power to ensure the long-term stable operation of each chip. A voltage conversion scheme based on the AMS1117 regulator is preferred, converting the 5V input voltage from the magnetic interface into a stable 3.3V output. This voltage output covers core components such as the main control chip, auxiliary processor, security chip, and universal serial bus control chip, ensuring that all components operate within the standard voltage range. This voltage regulation method not only reduces the impact of power fluctuations on system stability but also balances cost and space utilization efficiency in component selection and placement.

[0042] Regarding the signal triggering mechanism, a designated pin of the main control chip is directly connected to the output of the Hall sensor. When the Hall sensor outputs a low level, it triggers the falling edge response mechanism of the corresponding pin on the main control chip, thereby entering the interrupt handling process. In this process, the main control chip prioritizes executing the connection status confirmation logic, and then performs subsequent power allocation and interface initialization operations if the conditions are met. By adopting an interrupt response method, the real-time performance of connection detection can be significantly improved, while reducing the processing burden of the system in the non-connected state.

[0043] In terms of power consumption management, a joint determination mechanism based on connection status and identification control signal is introduced. The main control chip only wakes up the auxiliary processor and initiates the data acquisition and processing flow when the magnetic connection is established and the identification control signal is low; otherwise, the auxiliary processor maintains a low-power state. This strategy effectively avoids increased energy consumption caused by ineffective operation, which helps extend the overall service life of the device.

[0044] Furthermore, regarding interface identification and role control, the identification control signal is connected to a designated pin of the main control chip, enabling dynamic configuration of data interaction roles. When the identification control signal is low, it indicates that the current connection is an external host device. At this time, the main control chip sends control information to the auxiliary processor via serial communication. The auxiliary processor then enters a slave data output state, transmitting the collected fingerprint and face image data to the external host via a universal serial bus. When the identification control signal is high, the auxiliary processor enters a sleep state, and the fingerprint and image acquisition devices stop working, thereby reducing overall power consumption.

[0045] In terms of security, a dual judgment mechanism combining physical detection signals and logical recognition signals effectively enhances the system's ability to identify abnormal operations. When the system detects a mismatch between a change in the magnetic attraction state and the identification control signal, it will determine this as an abnormal connection and trigger protective measures, such as interrupting power supply, suspending data transmission, or recording the abnormal event. This strategy is of great significance in preventing malicious hot-plugging and unauthorized access.

[0046] In summary, through the collaborative design of multiple stages including magnetic field sensing, level determination, logic verification, power regulation, and role control, a stable, low-power, and safe magnetic connection detection and power activation mechanism has been constructed. This mechanism ensures connection reliability while providing a solid foundation for subsequent biometric collection and fusion authentication.

[0047] During the identity authentication process, fingerprint and facial information collection serve as the core input links for dual-mode recognition. Through the coordinated efforts of the main control chip, auxiliary processing chip, universal serial bus control chip, and security chip, a complete data acquisition, transmission, and processing path is formed.

[0048] Regarding fingerprint information acquisition, when a user enters the authentication state, the main control chip first initiates the fingerprint acquisition process based on the current connection and operating status. The main control chip sends control information to the auxiliary processing chip via corresponding communication pins to trigger the fingerprint data acquisition action. Upon receiving this control information, the auxiliary processing chip immediately enters the data acquisition stage, connecting to the universal serial bus control chip via its peripheral pins, thereby establishing a data interaction path with the fingerprint acquisition device. In this path, the fingerprint acquisition device acquires an image of the area touched by the user's finger and converts the acquired fingerprint texture information into a digital signal, which is then transmitted to the auxiliary processing chip via the universal serial bus control chip.

[0049] During data transmission, the universal serial bus control chip is responsible for signal format conversion and transmission scheduling to ensure data compatibility and stability across different devices. After receiving the fingerprint image data, the auxiliary processing chip performs preliminary data processing and buffering, and then transmits the fingerprint data back to the main control chip via a predetermined communication path. During this transmission, bidirectional communication pins are used for data exchange to ensure the integrity and continuity of data transmission.

[0050] After acquiring the fingerprint image data, the main control chip immediately calls upon the security chip for processing. The fingerprint image data is transmitted to the security chip for analysis via a serial communication interface. During this process, the security chip extracts features from the fingerprint image, identifying key features such as endpoints and intersections, and performs matching verification based on pre-stored templates. Simultaneously, the security chip combines the fingerprint image's grayscale distribution with physiological feature changes to determine liveness, thereby distinguishing between genuine and forged fingerprints. After completing the above processing, the security chip outputs the fingerprint authentication result and feeds back the relevant processing results to the main control chip.

[0051] For facial recognition data acquisition, the process follows a collaborative model consistent with fingerprint acquisition. Once the user's face enters the acquisition range, the image acquisition device begins acquiring the facial image and related dynamic information. This image data is transmitted to the auxiliary processing chip via the data pins of the Universal Serial Bus (USB) control chip. During transmission, the USB control chip manages the data transmission channel, forwarding image data in real time to ensure that image information is not lost or distorted during transmission.

[0052] After receiving facial image data, the auxiliary processing chip organizes it and sends it to the main control chip via a predetermined communication interface. Upon acquiring the facial data, the main control chip, following the same process as fingerprint processing, transmits the facial image data to the security chip for further processing. When processing facial data, the security chip first identifies key regions in the image, including eye position, mouth position, and facial contours, and extracts corresponding feature parameters. Based on this, the security chip performs liveness detection through multi-frame image analysis, such as recognizing blinking or head posture changes, to determine whether the current facial data originates from a real individual.

[0053] After completing liveness detection and feature extraction, the security chip compares the extracted facial features with pre-stored facial templates and outputs the matching result. If the matching result meets preset conditions, the security chip generates the corresponding facial authentication result and further generates a dynamic token. This dynamic token is generated based on time information and random factors in the current authentication process to enhance the security of the authentication process.

[0054] During the dual-mode fusion phase, the security chip jointly evaluates the fingerprint authentication result and the facial recognition result. Authentication is successful when both meet the authentication criteria; otherwise, an exception handling process is initiated. This dual-evaluation mechanism effectively improves the overall authentication accuracy and security level.

[0055] Regarding the authentication result output, the security chip encrypts the final authentication result and dynamic token to prevent data interception or tampering during transmission. After encryption, the relevant data is forwarded from the main control chip to the auxiliary processing chip, and then transmitted to the external device via the magnetic interface data pin through the output pin of the auxiliary processing chip and the universal serial bus interface. During this transmission process, the data path undergoes multi-level control and verification to ensure the stability and security of the transmission process.

[0056] Overall, through the division of labor and cooperation between the main control chip and auxiliary processing chip, the unified access of the universal serial bus control chip, and the deep involvement of the security chip, a complete path for biometric data acquisition, processing, verification, and output is formed. In this path, various signals are transmitted step-by-step in a predetermined order, ensuring not only the continuity of data processing but also providing strong support in terms of recognition accuracy and security protection. Simultaneously, the fusion of dual-mode data further reduces the risk of misjudgment caused by a single recognition method, thereby achieving a more reliable identity authentication effect.

[0057] In the dual-mode biometric fusion authentication process, the overall process revolves around four consecutive stages: detection preparation, liveness determination, feature comparison, and result fusion. Each stage proceeds step by step in chronological order and forms a sequential relationship at the data level, thereby ensuring the integrity and consistency of the authentication process.

[0058] During the test preparation phase, once the interface connection status is confirmed and the power supply is in a stable output state, the system enters the initial preparation process. At this time, all processing chips and acquisition devices are in normal operating condition, internal communication paths remain unobstructed, and data transmission conditions meet requirements. The main control side performs a rapid check of the current operating environment, including power supply status, signal stability, and the response of each device, to ensure that subsequent acquisition and processing can be carried out under stable conditions. This preparation process avoids directly entering the testing phase before the equipment is fully ready, thereby reducing the probability of anomalies.

[0059] During the liveness detection phase, the standby status of the devices is first confirmed. The operational status of the fingerprint and image acquisition devices is checked to determine if they are in a responsive state. The fingerprint acquisition device maintains continuous sensing capability of the contact area, while the image acquisition device remains in an image acquisition readiness state. After confirming that both types of acquisition devices are operational, the preliminary biometric detection process begins.

[0060] During the initial detection process, user actions are perceived to determine whether the input meets the acquisition conditions. On the fingerprint side, changes in the contact signal in the pressing area are detected to determine whether the finger is effectively contacting the acquisition area; on the face side, target recognition within the image acquisition range is used to determine whether the user's face has entered the valid acquisition area. When both types of detection results meet the preset conditions, the system enters the image acquisition process; if either condition is not met, the system waits or prompts for adjustment, thereby preventing invalid data from entering subsequent processing.

[0061] During biometric image acquisition, the fingerprint acquisition device obtains fingerprint texture images and converts them into digital image data; the image acquisition device simultaneously acquires facial image information. In this process, the system performs basic checks on the clarity, integrity, and contrast of the acquired images to ensure that the image quality meets processing requirements. This synchronous acquisition method maintains consistency between fingerprint and facial data over time, which is beneficial for subsequent fusion processing.

[0062] In the liveness detection stage, the collected image data is analyzed to determine whether it originates from a real individual. On the fingerprint side, the image grayscale distribution and feature point structure are combined to analyze texture details, distinguishing between real skin features and those of imitation materials. On the face side, dynamic behaviors such as blinking and head orientation changes are identified through continuous image changes to determine the presence of real living organism characteristics. If either detection result indicates non-real input, the process terminates or enters anomaly handling; if both types of detection pass, the feature comparison stage begins.

[0063] In the feature comparison stage, the first step is to extract features from the acquired valid image data. On the fingerprint side, key feature information such as endpoints and bifurcation points are extracted from the image to form a feature set. On the face side, geometric features of key facial regions are extracted, including eye position, mouth contour, and overall facial morphology parameters. After feature extraction, the extracted feature information is compared with pre-stored template data.

[0064] During the comparison process, the system calculates the matching degree between fingerprint features and the template, as well as the matching degree between facial features and the template, and makes judgments based on preset thresholds. When the matching degree meets the requirements, the corresponding recognition result is judged as passed; otherwise, it is judged as failed. After completing the independent comparison of the two types of features, the comparison results are comprehensively judged. If both types of results meet the conditions, the process proceeds to the next stage; if either condition is not met, the process enters the exception handling procedure.

[0065] During the result fusion and output stage, fingerprint and facial recognition results are integrated. When both types of recognition results pass, the system determines overall authentication is successful; if either recognition result fails, an exception handling mechanism is triggered. During exception handling, different strategies are adopted based on the specific reason. For example, if the image quality is insufficient, the user is prompted to adjust their position and re-capture the image; if a single recognition fails, the corresponding recognition method is allowed to be retried; and if the device malfunctions, error information is recorded and the current process is stopped.

[0066] During the final result processing, the system records and outputs the authentication results. For successful authentication, the success information is stored and the authentication result is output via the interface; for failed authentication, corresponding log information is generated and the failure status is sent via the interface. During data output, encryption methods can be used to protect the result data, thereby preventing unauthorized acquisition or tampering during transmission.

[0067] The overall process proceeds step-by-step through multiple stages, organically combining status detection, data acquisition, liveness detection, feature recognition, and result output. Each stage is tightly integrated through a unified data interface and control logic, thereby ensuring recognition accuracy while improving system stability, and enhancing adaptability to complex application environments through an exception handling mechanism.

[0068] In the dual-mode biometric authentication process, the interaction between the security chip and the main control chip plays a crucial role in data protection, liveness detection, and enhancing authentication credibility. The entire interaction process revolves around multiple stages, including initialization, self-test verification, data encryption, liveness detection, and dynamic token generation. These stages are sequentially connected through standard communication interfaces, forming a complete security processing loop.

[0069] During the initialization phase, after the system has stabilized its power supply and configured its interfaces, the main control chip establishes a communication connection with the security chip via a serial communication interface. This communication interface uses a standard synchronous serial communication method, transmitting data and clock signals through designated pins. The main control chip first sends initialization control information to the security chip to trigger its internal self-test process. During this process, the security chip performs a comprehensive check of its own operating status, including its internal storage status, processing unit status, and security protection mechanism status.

[0070] After completing the self-test, the security chip returns the test results to the main control chip via the communication interface. When the returned result is normal, the main control chip proceeds to the next processing step; when the returned result contains an anomaly flag, the main control chip records the anomaly information and can execute corresponding processing strategies, such as re-initializing or interrupting the current process. Through this initialization and self-test mechanism, potential problems can be identified in advance during the system startup phase, thereby improving overall operational reliability.

[0071] During the data encryption processing phase, the main control chip transmits the collected biometric data to the security chip. The biometric data includes fingerprint image data and facial feature data. During data transmission, a unified data frame format is used for encapsulation to ensure data integrity. After receiving the raw data, the security chip calls its internal encryption algorithm to process the data. The encryption process uses a symmetric encryption method, employing a high-strength key to encrypt the data, thereby generating ciphertext data.

[0072] After encryption, the security chip further protects the integrity of the encrypted data by generating a corresponding digital signature using an asymmetric algorithm. This digital signature, calculated based on the encrypted data and a preset key, can be used to verify whether the data has been altered during transmission. Subsequently, the security chip combines the encrypted data with the digital signature and returns it to the main control chip. Upon receiving this combined data, the main control chip can either forward it directly or use it for subsequent processing, thus establishing an effective anti-tampering mechanism in the data transmission path.

[0073] During the data verification phase, the security chip also participates in the processing when verification of received data is required. The main control chip transmits the data to be verified to the security chip, which decrypts the data and performs consistency verification in conjunction with the digital signature. During the verification process, if the data matches the signature, the data is deemed complete; if inconsistencies exist, it is determined that the data may have been interfered with or tampered with, thus triggering an exception handling procedure. Through the combination of this encryption and verification mechanism, dual protection of data can be achieved during transmission and storage.

[0074] In the liveness detection process, the main control chip sends a liveness detection request to the security chip via a communication interface. Upon receiving the request, the security chip invokes its internally pre-built liveness analysis methods to comprehensively analyze the input biometric data. On the fingerprint side, it analyzes the image's grayscale distribution, texture continuity, and subtle changes to identify whether it possesses genuine physiological characteristics. On the face side, it dynamically analyzes multiple frames of images to identify behavioral features such as blinking and changes in head posture, thereby determining whether the input data originates from a real individual.

[0075] After completing the liveness analysis, the security chip generates a corresponding liveness assessment result and returns it to the main control chip in numerical form. This assessment result can be represented as a continuous numerical range. By comparing it with a preset threshold, the main control chip can determine whether the current input meets the liveness requirements. When the assessment result reaches the set range, it is determined to be a genuine input; when the assessment result is below the threshold, it is determined to be a non-genuine input; when it is in the intermediate range, a supplementary detection process can be triggered. By introducing a quantitative assessment method, the flexibility and accuracy of liveness determination can be improved.

[0076] During the dynamic token generation phase, the main control chip sends a token generation request to the security chip. Upon receiving the request, the security chip combines the current time information, a random number, and an internally preset key, and performs a hash algorithm to generate a fixed-length dynamic token. This dynamic token is time-sensitive and unpredictable, serving as a secure credential for authentication results.

[0077] The generated dynamic token is returned to the main control chip via the communication interface, and the main control chip sends it to the external control terminal within a valid time frame. At the external control terminal, the received token is verified using the same calculation method to confirm the authenticity and integrity of the authentication result. This dynamic token mechanism effectively prevents replay attacks and forgery, further enhancing the security of the authentication process.

[0078] Overall, through the coordinated operation of multiple stages, including initialization self-test, encryption processing, data verification, liveness detection, and dynamic token generation, a close interactive relationship is formed between the security chip and the main control chip. During this interaction, data undergoes status verification before entering the processing stage, is protected by encryption during processing, and has enhanced security through a token mechanism during output, thus constructing a complete and reliable security processing flow.

[0079] This technical solution has good versatility and scalability, and can be deployed in multiple application scenarios with high requirements for identity authentication security and convenience, specifically in the following aspects: In the financial payment sector, it can be widely used in various self-service terminal devices, such as bank self-service terminals, ATMs, and mobile transaction processing devices. In these scenarios, the fusion authentication method using fingerprint and facial information can effectively improve the accuracy and security level of user identity verification, reducing the risks associated with traditional single authentication methods. Furthermore, the magnetic connection facilitates rapid replacement and maintenance of the authentication components, making it suitable for high-frequency use and long-term operating environments.

[0080] In the field of mobile terminal devices, it can be adapted to laptops, tablets, and related portable smart terminals to expand user authentication functions. Through external magnetic authentication components, dual biometric recognition capabilities can be added to the terminal without altering the original device structure, thereby enhancing the device's security performance in data protection and access control. Furthermore, this method is also suitable for peripheral expansion scenarios for smartphones, providing flexible support for diverse applications.

[0081] In the fields of identity verification and government services, this technology can be applied to environments such as examination supervision, self-service government processing, and public service terminals. In these scenarios, the authentication process often requires high accuracy and resistance to identity theft. Through dual-mode liveness detection and fusion judgment mechanisms, identity fraud can be effectively prevented. Simultaneously, in smart home and IoT applications, this technical solution can serve as a unified identity portal, enabling secure access control to multiple devices.

[0082] In enterprise office and attendance management, this technology can be used in scenarios such as employee attendance systems, access control of confidential documents, and warehouse management. Through integrated authentication methods, it ensures consistency between personnel identity and access permissions, reducing management risks. In remote or distributed office environments, this solution can also serve as an important means of identity verification, providing reliable protection for system login and resource access.

[0083] This invention enhances the reliability of identity verification by integrating fingerprint and facial recognition within the same authentication process, combined with liveness detection and dynamic token mechanisms. The simultaneous collection and comparison of both biometric features effectively reduces the risk of misjudgment from a single identification method. Furthermore, the liveness detection step verifies the authenticity of the input source, making the authentication results more reliable and stable, thereby improving the overall security level.

[0084] This invention utilizes a magnetic interface for rapid connection and automatic identification, simultaneously performing status detection and power supply control during device connection, ensuring a smoother system startup. Through a unified data transmission path and interface design, it reduces operational complexity during connection and supports convenient disassembly and maintenance in subsequent use, thereby improving device efficiency, reducing maintenance costs, and enhancing adaptability in various scenarios.

[0085] This invention provides Figure 1-7 A dual-mode biometric fusion security authentication system based on magnetic coupling includes a magnetic attraction detection module, a data acquisition and processing module, a liveness feature extraction module, a feature matching authentication module, and an encrypted transmission verification module. The magnetic attraction detection module, when the magnetic attraction interface enters the connection range and establishes a connection, outputs a magnetic field change signal with the help of the Hall element. The main controller combines the recognition control signal to complete the connection determination, and supplies power to the fingerprint acquisition device and the image acquisition device through the magnetic attraction interface. At the same time, it completes the data interface configuration of the auxiliary processor. The data acquisition and processing module, after completing connection determination and interface configuration, sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. The liveness feature extraction module, based on the acquired fingerprint image data and face image data, uses the main controller to call the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint features and face features; The feature matching and authentication module compares the valid fingerprint features and facial features with the pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. The encrypted transmission verification module combines the authentication result with the dynamic token. The security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process.

[0086] The magnetically coupled dual-mode biometric fusion security authentication method provided in this embodiment of the invention is implemented through the above-mentioned magnetically coupled dual-mode biometric fusion security authentication system. For details of the specific methods and processes of the magnetically coupled dual-mode biometric fusion security authentication system, please refer to the above-mentioned embodiment of the magnetically coupled dual-mode biometric fusion security authentication method, which will not be repeated here.

[0087] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A dual mode biometric fusion security authentication method based on magnetic coupling, characterized in that, Includes the following steps: When the magnetic interface enters the connection range and establishes a connection, the Hall element outputs a magnetic field change signal. The main controller combines the recognition control signal to complete the connection determination and supplies power to the fingerprint acquisition device and image acquisition device through the magnetic interface. At the same time, it completes the data interface configuration of the auxiliary processor. After completing the connection determination and interface configuration, the main controller sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. Based on the acquired fingerprint and face image data, the main controller calls the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint and face features. Based on valid fingerprint features and facial features, the security chip matches and compares them with pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. Combining the authentication result with the dynamic token, the security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process.

2. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 1, wherein, The steps to refine the magnetic connection status recognition process and improve the stability and accuracy of connection determination are as follows: As the magnetic interface enters the sensing range, the Hall element continuously outputs a magnetic field change signal and records the duration of the signal change; The main controller continuously samples the magnetic field change signal and judges the stability of the sampling results; When the sampling signal remains consistent within a set time range, connection confirmation is completed in conjunction with the identification control signal. When the connection confirmation result is successful, the power supply control and data interface configuration process is triggered to complete the stable connection determination.

3. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 2, wherein, To standardize the acquisition process of fingerprint and facial images and improve data collection consistency, the following steps are taken: After the main controller sends out the acquisition control information, the auxiliary processor establishes a communication path with the universal serial bus; Fingerprint image data and face image data are received separately through the communication path; Perform integrity checks on the received data and mark any abnormal data. The verified image data is transmitted to the main controller to form standardized input data.

4. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 3, wherein, To enhance the reliability of liveness detection and improve the quality of biometric recognition, the following steps are taken: Gray-scale distribution analysis was performed on the fingerprint image, and texture detail information was extracted; Perform multi-frame continuous analysis on facial images to extract dynamic change information; Input texture detail information and dynamic change information into the liveness detection process separately; Based on the detection results, valid fingerprint and facial features are selected for subsequent comparison processing.

5. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 4, wherein, A partitioned gradient sequence is formed for the grayscale distribution and continuous texture changes are extracted. A time change trajectory is established for multiple frames of images and stable dynamic features are extracted. The two types of features are synchronized and consistency judgment is performed. Only features that simultaneously meet the requirements of texture continuity and dynamic response are retained for comparison processing.

6. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 4, wherein, The steps to standardize the feature comparison process and improve the consistency of authentication results are as follows: The extracted fingerprint and facial features are formatted and organized. Each matching calculation is performed with a pre-stored template to obtain the corresponding matching result; Threshold determination is applied to the matching results to determine their respective recognition status; When both fingerprint recognition and facial recognition status meet the requirements, a unified authentication result is output.

7. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 6, wherein, The following steps are taken to strengthen the security protection of authentication results and improve the security of data transmission: After the authentication result is generated, the result data is combined with the dynamic token to form the data to be processed; The security chip performs encryption processing on the data to be processed; The encrypted data is marked with an integrity verification tag; The processed data is then transmitted to an external device via an auxiliary processor.

8. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 7, characterized in that, Once the result data and dynamic token are combined to form the data to be processed, the security chip performs encryption operations on the data to be processed and simultaneously generates verification information; the encryption result and verification information are then bound together to form associated data. During transmission, the associated data undergoes consistency verification; if the verification passes, the data is output to an external device via an auxiliary processor.

9. The dual mode biometric fusion security authentication method based on magnetic coupling according to claim 7, wherein, The following steps were taken to improve the connection status verification mechanism during the authentication process and enhance the stability of the system: Continuously receive magnetic connection status signals during data transmission; Real-time monitoring of changes in connection status signals; When an abnormal change in connection status is detected, the abnormal information is recorded and the current data transmission is interrupted; Once the connection status stabilizes, the authentication process is restarted, thus completing the closed loop of status verification.

10. A magnetically coupled dual-mode biometric fusion security authentication system, used to implement the magnetically coupled dual-mode biometric fusion security authentication method according to any one of claims 1-9, characterized in that, It includes a magnetic attraction detection module, a data acquisition and processing module, a liveness feature extraction module, a feature matching and authentication module, and an encrypted transmission verification module. The magnetic attraction detection module, when the magnetic attraction interface enters the connection range and establishes a connection, outputs a magnetic field change signal with the help of the Hall element. The main controller combines the recognition control signal to complete the connection determination, and supplies power to the fingerprint acquisition device and the image acquisition device through the magnetic attraction interface. At the same time, it completes the data interface configuration of the auxiliary processor. The data acquisition and processing module, after completing connection determination and interface configuration, sends acquisition control information to the auxiliary processor. The auxiliary processor acquires fingerprint image data and face image data via the universal serial bus and transmits the acquired data to the main controller. The liveness feature extraction module, based on the acquired fingerprint image data and face image data, uses the main controller to call the security chip to perform liveness detection and feature extraction processing, and outputs valid fingerprint features and face features; The feature matching and authentication module compares the valid fingerprint features and facial features with the pre-stored templates. When the comparison meets the conditions, it outputs the authentication result and generates the corresponding dynamic token. The encrypted transmission verification module combines the authentication result with the dynamic token. The security chip encrypts the relevant data and transmits it through the magnetic interface via the auxiliary processor. At the same time, it performs status verification based on the connection determination result to complete the authentication process.

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