Biometric information processing method based on biometric recognition, and related apparatus

Abstract

A biometric information processing method based on biometric recognition, which method is applied to a client, wherein the client runs on a mobile terminal. The method comprises: detecting an instruction for indicating activation of at least two cameras to respectively collect biometric information (S210); in response to the instruction, activating the at least two cameras associated with a mobile terminal, in order to respectively obtain images containing biometric information that are acquired by the cameras (S220); and sending to a server side the images containing biometric information that are acquired by the cameras, such that the server side identifies the biometric information contained in the images to obtain at least two types of biometric information, and associating the at least two types of biometric information with the same user identifier (S230).

Description

Biometric-based biometric information processing methods and related devices

[0001] Related applications

[0002] This application claims priority to Chinese patent application filed on November 13, 2024, with application number 202411624058.3, entitled "Biometric Information Processing Method and Related Device Based on Biometrics", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of biometrics technology, specifically to a biometrics-based biometrics-based biometrics processing method and related apparatus. Background Technology

[0004] Biometric technology is a technology that closely integrates computers with high-tech methods such as optics, acoustics, biosensors, and biostatistics to identify individuals using their inherent physiological characteristics and behavioral features. Types of biometrics mainly include facial recognition, fingerprint recognition, iris recognition, voiceprint recognition, palmprint recognition, and finger vein recognition.

[0005] Regardless of the type of biometric system, users need to register their biometric information in advance. Currently, users mainly input their biometric information by operating specific devices or mobile terminals. The former is inconvenient and increases costs, thus limiting the popularization and development of biometric technology. The latter solves the problems of convenience and cost, but cannot adapt to scenarios that require rapid registration and verification of multiple biometric information.

[0006] Therefore, there is an urgent need to propose a bioinformatics processing solution that can meet the needs of rapidly completing registration and verification of multiple biometric information. Summary of the Invention

[0007] Embodiments of this application provide a biometric-based biometric information processing method, a biometric-based biometric information processing device, an electronic device, a computer-readable storage medium, and a computer program product.

[0008] One aspect of this application provides a biometric information processing method based on biometrics, applied to a client running on a mobile terminal. The method includes: detecting an instruction to enable at least two cameras to collect biometric information respectively; responding to the instruction, activating at least two cameras associated with the mobile terminal to obtain images containing biometric information collected by each camera respectively; and sending the images containing biometric information collected by each camera to a server, so that the server can identify the biometric information contained in each image, obtain at least two types of biometric information, and associate the at least two types of biometric information with the same user identifier.

[0009] In another aspect of this application, a biometric information processing device based on biometrics is provided. The device includes: a detection module configured to detect an instruction to enable at least two cameras to collect biometric information respectively; a collection module configured to, in response to the instruction, activate at least two cameras associated with a mobile terminal to obtain images containing biometric information collected by each camera respectively; and a processing module configured to send the images containing biometric information collected by each camera to a server, so that the server identifies the biometric information contained in each image, obtains at least two types of biometric information, and associates the at least two types of biometric information with the same user identifier.

[0010] Another aspect of this application provides an electronic device, including: one or more processors; and a memory for storing one or more computer programs, which, when executed by the one or more processors, cause the electronic device to implement the biometric-based bio-information processing method as described above.

[0011] Another aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor of an electronic device, causes the electronic device to perform the biometric-based biometric information processing method as described above.

[0012] Another aspect of this application provides a computer program product, including a computer program that, when executed by a processor of an electronic device, implements the biometric-based biometric information processing method described above.

[0013] Details of one or more embodiments of this application are set forth in the following drawings and description. Other features, objects, and advantages of this application will become apparent from the specification, drawings, and claims. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the published drawings without creative effort.

[0015] Figure 1 is a schematic diagram of an implementation environment involved in this application;

[0016] Figure 2 is a flowchart illustrating a biometric-based biometric information processing method according to an exemplary embodiment of this application;

[0017] Figure 3 is a flowchart illustrating a biometric-based biometric information processing method in another exemplary embodiment of this application;

[0018] Figure 4 is a schematic diagram of an exemplary image preview interface;

[0019] Figure 5 is a schematic diagram of an exemplary application scenario shown in this application;

[0020] Figure 6 is a schematic diagram of the overall timing corresponding to the application scenario shown in Figure 5;

[0021] Figure 7 is a flowchart illustrating a biometric-based biometric information processing method in another exemplary embodiment of this application;

[0022] Figure 8 is a block diagram illustrating a biometric-based biometric information processing device according to an exemplary embodiment of this application;

[0023] Figure 9 shows a schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0026] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0028] In this application, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0029] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0030] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0031] Please refer to Figure 1 first, which is a schematic diagram of an implementation environment involved in this application. This implementation environment specifically illustrates an application scenario in which a user registers facial information and palm print information simultaneously using a mobile terminal 110, including the mobile terminal 110 and the server 120, with a wired or wireless communication connection pre-established between the mobile terminal 110 and the server 120.

[0032] Mobile terminal 110 can be used with smartphones, tablets, and other smart devices equipped with a rear camera 101 and a front camera 102. It uses the rear camera 101 to capture the user's palm print image and the front camera 102 to capture the user's face image, thus simultaneously completing the registration and verification of both facial and palm print information. This not only meets the needs of scenarios requiring rapid registration and verification of both facial and palm print biometric information but also maintains convenience and eliminates the need for additional hardware costs.

[0033] Mobile terminal 110 can also be a smart device such as a laptop computer with a built-in camera to register facial and palm print information simultaneously, but this requires an external camera connected to the smart device. Therefore, while it can meet the needs of scenarios requiring rapid registration and verification of dual biometric information (facial and palm print), it is less convenient and requires additional hardware costs.

[0034] Mobile terminal 110 can also be a smart device without its own camera, but it supports connecting at least two external cameras to collect the user's facial and palm print information separately. While this can meet the needs of registration and verification scenarios requiring rapid completion of both facial and palm print biometric information, it is less convenient and requires higher hardware costs.

[0035] Server 120 receives a face image and a palm print image sent by mobile terminal 110, and identifies the facial information contained in the face image and the palm print information contained in the palm print image. During the registration phase, server 120 binds the identified face and palm print information to the user account; during the verification phase, server 120 verifies the user's identity based on the identified face and palm print information. If both the face and palm print information pass verification, the verification is considered successful.

[0036] It should be noted that server 120 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services; no restrictions are imposed here.

[0037] Please refer to Figure 2, which is a flowchart illustrating a biometric-based biometric information processing method according to an exemplary embodiment of this application. This method can be applied to the implementation environment shown in Figure 1, specifically executed by the mobile terminal 110, or jointly executed by the mobile terminal 110 and the server 120. Of course, this method can also be applied to other implementation environments and executed by mobile terminals in other implementation environments, or jointly executed by the mobile terminal and the server; this embodiment does not impose any limitations.

[0038] It should be noted that the biometric information processing method based on biometrics provided in this embodiment is applied to a client, and the client runs on a mobile terminal. The mobile terminal is associated with at least two cameras, and the client can control the simultaneous opening of at least two cameras to capture images containing biometric information through each camera, and upload at least two captured images to the server for identification and processing of the biometric information contained in the at least two images on the server.

[0039] As shown in Figure 2, in an exemplary embodiment, the biometric-based biometric information processing method includes steps S210-S230, which are described in detail below:

[0040] S210, Detects instructions used to instruct the activation of at least two cameras to collect biological information separately.

[0041] The client can detect instructions to simultaneously activate at least two cameras to collect biological information. In this embodiment, there are no restrictions on how the client detects these instructions.

[0042] For example, a specific operation entry point is set on the user interface of the client. When the user triggers this operation entry point, the client maps the triggering event of the operation entry point to an instruction to activate at least two cameras to collect biological information, according to a preset mapping rule. The preset mapping rule can be: to map the unique identifier of the operation entry point to the code of the instruction one-to-one. When the operation entry point is detected to be triggered, the client looks up the corresponding instruction code in a pre-established mapping table based on its unique identifier and generates the corresponding instruction. The mapping table stores the one-to-one correspondence between the unique identifier of the operation entry point and the instruction code.

[0043] For example, an external device can send specific trigger information to a mobile terminal. When the client detects this trigger information, it converts it into an instruction to activate at least two cameras to collect biological information according to a preset conversion algorithm. Alternatively, the external device can directly send this instruction to the mobile terminal. In other embodiments, the client can also detect an instruction to activate at least two cameras to collect biological information within a specified time range. The specified time range can be a fixed duration, specifically a very short duration, such as 1 second. The preset conversion algorithm can be: parsing the trigger information, extracting key features such as specific character combinations or number sequences, matching these key features with a predefined instruction template, and generating a corresponding instruction if a match is successful. The predefined instruction template stores the correspondence between key features and instructions.

[0044] The camera mentioned in this embodiment is generally a composite structure camera. A composite structure camera is a device for acquiring images, formed by combining multiple components, generally including a lens, an image sensor, a digital signal processing chip, etc. If the camera components are classified based on the type of image acquired, it can be implemented by one or a combination of depth camera components, infrared camera components, and color camera components.

[0045] A depth camera component is a part of a composite camera system used to collect distance information between objects in a scene and the camera, thereby generating a depth image. Its working principle can be based on optical ranging, emitting infrared light and receiving the reflected signals to calculate the depth value of each pixel; alternatively, it can use at least two cameras to capture the same scene from different angles, calculating depth information by matching feature points from different viewpoints; or it can use machine learning algorithms such as deep convolutional neural networks to predict depth information from single or multiple color images.

[0046] The infrared camera component is a part of a composite camera system. It generates infrared images by capturing the infrared radiation emitted by objects in a scene. It senses and converts infrared radiation into electrical signals through an installed infrared sensor. The sensor's output electrical signals are then amplified, filtered, and digitally converted to enhance signal quality and facilitate subsequent image processing. Finally, the processed digital signal is converted into an infrared image.

[0047] The color camera component is a part of the composite structure camera. It captures light through an image sensor installed in the camera and converts it into electrical signals, which are then processed to obtain a color image.

[0048] S220, in response to the instruction, activate at least two cameras associated with the mobile terminal to obtain images containing biological information captured by each camera.

[0049] When the client detects an instruction to enable at least two cameras to collect biological information, it responds to the instruction by activating at least two cameras associated with the mobile terminal, thereby obtaining images containing biological information collected by each camera.

[0050] It's important to understand that, technically, the client should have at least two cameras activated simultaneously to collect at least two types of biometric information at the same time. However, since the "simultaneous" mentioned in this embodiment emphasizes the technical effect—that is, using different cameras to collect different types of user biometric information at once in a single operation, such as facial and palm print biometrics—the requirement that at least two cameras be activated at the same time is not an absolute condition. As long as the time interval between the activation of at least two cameras does not affect the simultaneous processing of at least two types of biometric information in the client, it is feasible to implement the system.

[0051] For example, the client can create at least two asynchronous view threads, each responsible for activating different cameras to acquire images. This ensures that a malfunction in one camera does not affect image acquisition by the others. Thus, by running each view thread, images containing biological information can be obtained from each camera independently.

[0052] Asynchronous view threads are threads created by the client to enable simultaneous image acquisition from multiple cameras. Each view thread is responsible for opening different cameras and acquiring images from each camera. By running these view threads, images containing biological information can be obtained from each camera independently, and a failure of one camera will not affect the image acquisition by the other cameras.

[0053] It is also important to understand that cameras themselves do not usually actively identify whether the images they capture contain biological information. However, since this application involves a biometric application scenario, after the client controls and activates at least two cameras, the user will inevitably cooperate in performing operations related to the collection of their own biological information. Therefore, the cameras can capture images containing biological information.

[0054] As an example implementation, when the client detects a shooting command, such as when the user triggers the shooting button on the client's user interface, or when the camera automatically generates a shooting command after being turned on for a specified period of time, it controls each camera to capture images.

[0055] As another exemplary implementation, the client initiates each camera to periodically capture images. After acquiring the images, pre-detection processing can be performed. For example, if a camera is used for capturing facial information, the client can perform face detection on the images captured by that camera. If a face is detected in the image, it means that an image containing facial information has been captured, and the client controls the camera to stop capturing images; otherwise, it controls the camera to continue capturing images. Similarly, if a camera is used for capturing palm print information, the client can detect whether the images captured by that camera contain a palm area, and then control whether the camera continues capturing images accordingly.

[0056] As another exemplary implementation, a selection program can also be installed in the client. This selection program performs selection processing on the biometric information to obtain an image containing the selected biometric information. Specifically, the client controls the camera to continuously capture images and performs selection on the continuously captured images based on preset biometric information selection conditions until a target image is obtained. The target image refers to an image containing valid biometric information, which can be understood as the biometric information that the client can successfully identify from the image.

[0057] The specific method by which the image selection program performs image selection can be as follows: For each captured image, it is evaluated and scored according to preset biometric information selection criteria. For example, for images captured by a camera used to collect facial information, if the preset biometric information selection criteria include at least one of color image selection, depth image selection, and infrared image selection, for color images, scores are given based on face angle, face size, face centering, and color image clarity, with different weights assigned to each indicator according to their importance; for depth images, scores are given based on completeness and accuracy; and for infrared images, scores are given based on brightness and contrast. The weighted sum of the scores is used to obtain a comprehensive score for the image, and the image with the highest comprehensive score is selected as the target image. The biometric information selection criteria are the basis for the selection program installed on the client to perform biometric information selection processing. Based on these criteria, images continuously captured by the camera are evaluated and scored to obtain images containing selected biometric information. Different types of biometric information collection correspond to different selection criteria.

[0058] For example, for images continuously captured by a camera used to collect facial information, the preset biometric optimization conditions may include at least one of color image optimization, depth image optimization, and infrared image optimization. The color image can be obtained by an image sensor deployed in the camera capturing light and converting it into an electrical signal, followed by signal processing. The color image optimization process may include optimization based on facial angle, facial size, facial centering, and color image sharpness, ensuring that the optimized target image guarantees the face is facing the camera directly, avoiding excessive angular deviation, and that the face is of appropriate size in the image for accurate facial feature recognition. The face should be centered in the image to reduce recognition errors caused by positional offset, and the image should be clear, with visible details, moderate contrast, and no overexposure or underexposure.

[0059] Depth maps are typically used to represent distance information between objects in a scene and a camera. For example, a camera based on optical ranging emits infrared light while capturing a color image and receives the reflected signal to calculate the depth value of each pixel, thus obtaining a depth image. Alternatively, at least two cameras capture the same scene from different angles, and depth information is calculated by matching feature points from different viewpoints, resulting in a depth image. Or, machine learning algorithms such as deep convolutional neural networks can be used to predict depth information from one or more color images to obtain a depth image. The process of optimizing a depth map can include optimization based on completeness and accuracy, ensuring that the depth map of the optimized target image completely covers the facial region, guaranteeing accurate acquisition of facial depth information. The depth information should accurately reflect the three-dimensional structure of the face, free from noise or erroneous depth values.

[0060] Infrared images are generated by cameras by capturing the infrared radiation emitted by objects in a scene. For example, a camera uses an infrared sensor to sense and convert infrared radiation into an electrical signal. The sensor's output signal is then amplified, filtered, and digitally converted to enhance signal quality and facilitate subsequent image processing, ultimately converting the processed digital signal back into an infrared image. The process of optimizing the infrared image may include optimization based on brightness and contrast. The optimized infrared image should have moderate brightness, clearly displaying facial features without being too bright and losing detail. The contrast should also be high enough for the algorithm to accurately distinguish the face from the background.

[0061] For images continuously captured by a camera used to collect palm print information, the preset biometric information preference conditions may include at least one of color image preference and infrared image preference.

[0062] It should be noted that while these exemplary implementations ensure that the client can acquire images containing biometric information through at least two cameras, they require relatively complex processing. Therefore, when the mobile terminal has high processing power, the client can use the processing resources provided by the mobile terminal to implement these implementations; conversely, when the mobile terminal does not have processing power advantages, the client can collaborate with the server to implement these implementations, and no limitations are imposed here.

[0063] S230, the images containing biological information captured by each camera are sent to the server so that the server can identify the biological information contained in each image, obtain at least two kinds of biological information, and associate the at least two kinds of biological information with the same user identifier.

[0064] The client sends images containing biological information captured by each camera to the server, which then identifies the biological information contained in the images, such as facial features and palm print features, thereby obtaining at least two types of biological information.

[0065] The server associates at least two types of biometric information with the same user identifier, and the implementation process varies depending on the application scenario. For example, in a biometric registration scenario, the server associates these at least two types of biometric information with the user's account identifier and stores them in a registered database; in a biometric verification scenario, the server searches the registered database to see if these at least two types of biometric information are associated with the user's account identifier, and if so, the verification is successful.

[0066] Therefore, the technical solution provided in this embodiment enables the simultaneous activation of at least two cameras associated with the mobile terminal to capture images containing biological information. The server then identifies and associates the biological information contained in each image, allowing the client to complete the registration of at least two types of biological information of the user at one time without increasing hardware costs. This significantly improves registration efficiency and convenience, thereby meeting the needs of scenarios requiring rapid completion of registration and verification of multiple biological information.

[0067] For example, in some exemplary embodiments, the mobile terminal is associated with at least two cameras: a front-facing camera and a rear-facing camera. The front-facing camera captures images containing facial information, while the rear-facing camera captures images containing palm print information. Users can simultaneously capture facial and palm print information without assistance, offering high operational convenience and a superior user experience. Furthermore, by capturing the user's facial and palm print information separately using the front and rear cameras, tasks that previously required multiple user actions can be completed in a single operation, significantly reducing user interaction time and improving overall registration and verification efficiency. Additionally, utilizing the existing front and rear cameras of the mobile terminal eliminates reliance on specific hardware, thus offering high adaptability and compatibility, and allowing for widespread application in various smartphones, tablets, and other devices.

[0068] In other exemplary embodiments, the mobile terminal has a front-facing camera and a rear-facing camera, and is also connected to an external camera. The client activates at least two cameras, including at least one of the front-facing and rear-facing cameras, and also includes the external camera. The external camera can be connected to the mobile terminal via USB (Universal Serial Bus) or wirelessly, and can work in conjunction with the mobile terminal's front and rear cameras. The external camera may be specifically designed for capturing high-precision biometrics, providing higher image quality than the mobile terminal's front and rear cameras, thereby offering higher precision and flexibility in biometric capture without being limited by the performance of the mobile terminal's built-in camera.

[0069] Please refer to Figure 3, which is a flowchart illustrating a biometric-based biometric information processing method in another exemplary embodiment of this application. Based on the embodiment shown in Figure 2, this method further includes steps S310-S330, which are described in detail below:

[0070] S310, when the registration entry on the bio-information registration interface displayed on the client is triggered, an instruction is generated to instruct at least two cameras to collect bio-information respectively.

[0071] In the embodiments of this application, users can complete the registration and verification of at least two types of biological information in a single operation by performing operations through the user interaction interface provided by the client. The biological information registration interface mentioned in this embodiment corresponds to the user interaction interface for implementing biological information registration. When a user triggers the registration entry on the biological information registration interface displayed by the client, it indicates that the user needs to register their own biological information. Therefore, the client generates instructions to activate at least two cameras to collect biological information respectively.

[0072] The S320 will jump to the image preview interface, and display the images captured by each camera together on the image preview interface.

[0073] The image preview interface is the interface that the client jumps to, used to display images captured by various cameras. This allows users to learn about registration-related information, such as whether the camera has captured an image containing their own biological information. Users can also adjust their posture based on the images displayed on the interface to obtain the preferred target image.

[0074] After generating a command to instruct at least two cameras to collect biometric information, the client responds by activating at least two cameras. This embodiment displays an image preview interface, showing images captured by each camera, allowing the user to access registration-related information. For example, the user can see if the camera has captured an image containing their own biometric information; if not, the user can adjust their posture to allow the camera to capture such an image. Alternatively, the user can adjust their posture based on the images displayed in the preview interface to enable the camera to quickly capture a preferred target image.

[0075] This embodiment does not limit the way images captured by at least two cameras are displayed on the image preview interface. For example, Figure 4 illustrates that images captured by at least two cameras are displayed vertically side-by-side on the image preview interface. Of course, images captured by at least two cameras can also be displayed horizontally side-by-side on the image preview interface, or in other ways.

[0076] In some embodiments, the client can also periodically detect the image quality of the images captured in real time by each camera, and display the image acquisition progress of each camera on the image preview interface based on the image detection results. Specifically, image quality detection can include evaluating various factors affecting image quality, such as exposure, sharpness, color, texture, and noise, and generating corresponding image quality detection results based on the evaluation results of each factor. Image quality can also be determined by combining the image optimization process. For example, one or more parameters involved in the color image optimization process, such as face angle, face size, face centering, and color image sharpness, as well as the completeness and accuracy involved in the depth image optimization process, and the brightness and contrast involved in the infrared image optimization process, can be used as factors affecting image quality.

[0077] Whether it's facial information collection or palm print information collection, since users adjust their posture based on the images displayed on the image preview interface, the capture of biometric information by each camera is usually becoming more and more precise, and the quality of the images collected by the cameras is also getting higher and higher. Therefore, the collection progress of each camera can be generated based on the image quality detection results.

[0078] Specifically, let Q be the quality detection result of the image captured in real time by the camera, and let Q be the set quality threshold. th If the data acquisition progress is P, then the formula for calculating the data acquisition progress is: Among them Q and Q th All are values ​​greater than 0. When Q ≥ Q th When the value of P is between 0 and 1, and the closer Q is to Q... th The larger P is, the more likely Q is to be; th When P is negative, it can be considered as 0 in practical applications.

[0079] A quality threshold is a standard used by the client to determine whether an image captured by the camera is a valid image. Images exceeding the quality threshold are considered valid images captured by the camera. The client can generate acquisition progress based on the difference between the quality detection result of the real-time images captured by the camera and the quality threshold. This difference is inversely proportional to the acquisition progress; the smaller the difference, the greater the acquisition progress. By setting a quality threshold, images exceeding the threshold are considered valid images captured by the camera. For the reasons mentioned above, the image quality captured by the camera usually increases over time. Therefore, acquisition progress can be generated based on the difference between the quality detection result of the real-time images captured by the camera and the quality threshold. This difference is inversely proportional to the acquisition progress; the smaller the difference, the greater the acquisition progress. The acquisition progress, generated by the client based on the difference between the quality detection result of the real-time images captured by the camera and the set quality threshold, represents the progress of the camera in acquiring biological information.

[0080] Therefore, this embodiment displays relevant information about the images captured by each camera by setting an image preview interface, making the biological information collection process clear at a glance and providing users with a good user experience.

[0081] S330: Based on the biological information feedback results returned by the server, register at least two types of biological information.

[0082] The bioinformatics feedback results are generated by the server based on the search results of at least two identified biometric data in the registered database. Specifically, let the at least two identified biometric data be B = {b1, b2, ..., b...}. n ​}, the user's account identifier is U, and the association between the biometric information stored in the registered database and the account identifier is R = {(b r1 ,u r1 ),(b r2 ,u r2 ),…,(b rm ,u rm The server retrieves each type of biometric information from the registered database. i Does (i = 1, 2, ..., n) have associated account identifiers? If for all b i If no associated account identifier exists in R, a feedback result of "All biometric information is unregistered" is generated; if some biometric information exists... i If an associated account identifier exists in R, but another part does not, a feedback result of "part of the biometric information has been registered, and the other part of the biometric information has not been registered" is generated; if all b i In R, all biometric information has an associated account identifier, but if the associated account identifier is inconsistent with U, then the feedback result "All biometric information has been registered, but the associated account identifiers are inconsistent" is generated; if all biometric information has an associated account identifier .... i If all biometric information has an associated account identifier in R, and the associated account identifier is U, then the feedback result "All biometric information has been registered, and the associated account identifiers are consistent" will be generated.

[0083] It is important to understand that if biometric information is associated with a user's account identifier in the registered database, it means that the biometric information has been registered.

[0084] Bioinformatics feedback results can include the following: none of the bioinformatics are registered; some bioinformatics are registered, and some are not; all bioinformatics are registered, but the associated account identifiers are inconsistent; and all bioinformatics are registered, and the associated account identifiers are consistent.

[0085] The client displays biometric feedback results and guides the user to register for at least two types of biometric information based on the specific type of the feedback results. When the client detects an instruction to register based on at least two types of biometric information, it sends the client's logged-in account identifier to the server, so that the server associates and stores the at least two types of biometric information with the client's logged-in account identifier in the registered database.

[0086] Depending on the content of the bioinformatics feedback results, the process by which the client guides the registration of at least two types of bioinformatics varies. If none of the bioinformatics are registered, the client's login account identifier is directly associated with at least two types of bioinformatics. If some bioinformatics are registered and others are not, the process first checks if the accounts associated with the registered bioinformatics match the client's login account identifier. If they match, the unregistered bioinformatics are associated with the client's login account identifier. If they don't match, the incorrect association information stored in the registration database is deleted, and all bioinformatics are associated with the client's login account identifier. If all bioinformatics are registered but the associated account identifiers are inconsistent, all bioinformatics are re-associated with the client's login account identifier. If all bioinformatics are registered and the associated account identifiers match, no action is required, or a "registered" or "already exists" message is displayed on the user interface.

[0087] In another exemplary embodiment, before sending the client's logged-in account identifier to the server, it is necessary to check whether the client is currently logged in with the account identifier. If not, it is also necessary to invoke the specified application associated with the client to log in to the client based on the account identifier logged in the specified application. That is to say, the account information logged in on the client is consistent with the account information logged in the specified application. Based on this association, the client can more conveniently log in to the account.

[0088] In other exemplary embodiments, considering that significant differences in image quality among different cameras could affect the server's accuracy in recognizing different biometric information, thus disrupting the process of associating biometric information with account identifiers, it's crucial to address this issue. For instance, if the image quality from a particular camera is too poor, the server might fail to identify the biometric information in one of the at least two images sent by the client, preventing normal registration. Restarting the camera to collect biometric information would require user intervention, further impacting user experience. Therefore, the inability of the server to recognize biometric information in images should be avoided as much as possible.

[0089] As an exemplary implementation, images containing biometric information can be preprocessed before the server identifies the biometric information, such as through color correction, denoising, and sharpening. The image preprocessing can be performed by either the server or the client; there is no limitation on this. Color correction can employ color space conversion methods, transforming the image from RGB to HSV color space, adjusting hue, saturation, and brightness, and then converting it back to RGB color space. Denoising can use Gaussian filtering or median filtering to smooth noise in the image. Sharpening can utilize the Laplacian operator or the Sobel operator to enhance the image's edges.

[0090] As another exemplary implementation, after the client activates the cameras, it can acquire ambient light information from each camera and adjust the camera parameters accordingly to ensure that the quality difference between images containing biological information acquired by different cameras meets preset requirements. Specifically, the adjustment strategy can be as follows: when the ambient light is low, increase the camera's ISO and extend the exposure time; when the ambient light is high, decrease the ISO and shorten the exposure time. Simultaneously, adjust the aperture size based on the uniformity of light to ensure the overall brightness and clarity of the image.

[0091] Ambient light information of a camera refers to the lighting conditions of the environment in which the camera captures images. This information can be obtained through devices such as light sensors installed in the camera, or it can be triggered by the user in the bio-information registration interface. For example, the bio-information registration interface can provide input ports for the ambient light information of different cameras, such as providing some ambient light level labels. When the user triggers the corresponding label, the client obtains the ambient light information of each camera accordingly.

[0092] As another exemplary implementation, the client can also optimize the camera's capture speed to ensure that the camera can capture high-quality facial and palm print images within the time the user remains still. For example, the client can adjust at least one shooting parameter of each camera, such as frame rate, shutter speed, exposure time, and resolution, according to actual needs. Shooting parameters refer to parameters that affect the image quality captured by the camera, including frame rate, shutter speed, exposure time, and resolution. Specific adjustments can be based on: adjusting the frame rate according to the estimated time the user remains still to ensure a sufficient number of images are captured within that time; adjusting the shutter speed and exposure time according to the ambient light intensity and image clarity requirements; and selecting an appropriate resolution according to the accuracy requirements of biometric recognition.

[0093] Therefore, the biometric processing solution further provided in this embodiment can ensure the accuracy of biometric identification by the server, thereby ensuring the success of integrated registration of multiple biometric information, avoiding users performing multiple operations, and further improving the user experience.

[0094] Figure 5 is a schematic diagram of an exemplary application scenario shown in this application. As shown in Figure 5, the mobile terminal is specifically a smartphone, which runs an instant messaging client and a registration client. The registration client realizes quick login of user accounts based on the instant messaging client. The registration client obtains an image containing facial information captured by the front camera and an image containing palm print information captured by the rear camera through a single user operation. It then sends the image containing facial information, the image containing palm print information, and the currently logged-in instant messaging account to the backend server, so that the backend server can recognize the facial information and palm print information, bind the facial information and palm print information with the instant messaging account, and return the registration result to the registration client.

[0095] Figure 6 is a schematic diagram of the overall timing of the application scenario shown in Figure 5. As shown in Figure 6, after logging into the instant messaging account in the registration client, the user uses the front and rear cameras to capture their face and palm. The registration client sends the face and palm images to the backend server, enabling the backend server to perform face recognition on the face image and palmprint recognition on the palm image, and determine whether the recognized face and palmprint information has been registered. After receiving the recognition and judgment results from the backend server, the registration client displays the information from the backend server on the user interface and guides the user to confirm the registration of face and palmprint information. When the user confirms the registration, the registration client sends the face, palmprint, and account information to the backend server, enabling the backend server to bind the face and palmprint information to the instant messaging account and return the registration result to the registration client, allowing the registration client to confirm that the registration has been successfully completed.

[0096] As can be seen from the above, users can register both their face and palm print in a single registration operation. This one-time dual registration of biometric information can significantly reduce user interaction time. For example, existing technologies require users to perform two registration operations to register their face and palm print separately, while the embodiments of this application only require one operation to register both facial and palm print biometric information. Moreover, by capturing different biometric information simultaneously by different cameras, the registration time for multiple biometric information can be shortened by at least half, thus significantly improving the overall registration efficiency. Users also do not need to switch between different registration modes during the registration process, resulting in a smoother overall experience and significantly improving the user experience.

[0097] Please refer to Figure 7, which is a flowchart illustrating a biometric-based biometric information processing method in another exemplary embodiment of this application. Based on the embodiment shown in Figure 2, this method further includes steps S710-S730, which are described in detail below:

[0098] S710, when it detects that the verification entry on the biometric verification interface displayed on the client is triggered, generates an instruction to instruct at least two cameras to collect biometric information respectively.

[0099] The biometric verification interface is the interface displayed on the client. When the verification entry on this interface is triggered, it means that the user needs to enable integrated verification. The client will generate instructions to enable at least two cameras to collect biometric information.

[0100] In this embodiment, the client is used not only to achieve integrated registration of at least two types of biometric information, but also to achieve integrated verification of at least two types of biometric information. When the verification entry on the biometric verification interface displayed on the client is triggered, it indicates that the user needs to enable integrated verification. Therefore, the client generates an instruction to simultaneously activate at least two cameras to collect biometric information.

[0101] S720, jumps to display the image preview interface, and displays the images captured by each camera together in the image preview interface;

[0102] The client jumps to the image preview interface, which displays images captured by each camera, allowing users to know the acquisition progress and adjust their posture based on the images previewed to more effectively obtain the target image.

[0103] S730 displays the biometric verification results returned by the server; when at least two types of biometric information match the registration information associated with the logged-in account identifier in the client, the biometric verification result indicates successful verification.

[0104] The biometric verification result returned by the server refers to the server's search in the registered database, after identifying at least two types of biometric information, to determine whether both types of biometric information are associated with the account identifier logged in on the client. Specifically, let the identified at least two types of biometric information be B = {b1, b2, ..., b...}. n The account identifier logged in on the client is U, and the association between the biometric information stored in the registered database and the account identifier is R = {(b r1 ,u r1 ),(b r2 ,u r2 ),…,(b rm ,u rm The server iterates through each type of biometric information.i (i = 1, 2, ..., n), check if (b) exists in R. i The relationship between b and U). If for all b i All of them can be found in R with corresponding (b) i If the result is "U", it means that at least two biometric information matches the registration information associated with the account identifier, thus generating a successful verification result; otherwise, a verification failure result is generated.

[0105] In some embodiments, to ensure that the biometric information captured by at least two cameras corresponds to a real user, a reminder message can be displayed on the biometric verification interface to remind the user that the collected biometric information must be their own. A liveness detection process can also be introduced before or during image capture. Liveness detection refers to a technique that verifies whether biometric information originates from a real biological individual by collecting biometric information. Since the at least two cameras activated in this embodiment are used to collect biometric information, they can be used to implement liveness detection. Specific detection methods can be as follows: For facial information collection, action liveness detection can be used, requiring the user to perform actions such as blinking, opening their mouth, and shaking their head. The camera captures the user's actions and analyzes their continuity and naturalness. For palmprint information collection, blood flow detection can be used, utilizing the near-infrared function of the camera to detect the flow of blood in the palm and determine whether it is a real palm. Blood flow detection is a technique used to verify whether palmprint information originates from a real biological individual. It uses the near-infrared function of the camera to detect the flow of blood in the palm; if normal blood flow is detected, it is determined to be a real palm.

[0106] For example, when facial information is collected through the front camera of a smartphone and palm print information is collected through the rear camera, the front and rear cameras can perform liveness detection separately. Only when both cameras pass the liveness detection can subsequent processing be performed, thereby further ensuring the security of biometric verification.

[0107] This embodiment can be applied to scenarios such as mobile payment and access control systems. In mobile payment scenarios, users need to use the front-facing camera of their smartphone to collect facial information and the rear-facing camera to collect palm print information. Only when both the face and palm print are verified can the payment be successfully completed, thereby improving the security of mobile payments. In access control system scenarios, users use the front-facing camera of their smartphone to collect facial information and the rear-facing camera to collect palm print information. Only when both the face and palm print are verified can the access control system be successfully unlocked, thereby improving the security of the access control system.

[0108] In another exemplary embodiment, as an extension, at least two biometric information of at least the same type can be collected using the same camera. For example, palm print information of both the left and right hands can be collected simultaneously using one of the cameras, thereby enhancing the flexibility and security of the biometric identification scheme.

[0109] Please refer to Figure 8, which is a block diagram illustrating a biometric-based biometric information processing device according to an exemplary embodiment of this application. This device can be applied to the implementation environment shown in Figure 1, specifically configured on a mobile terminal, or jointly configured on mobile terminal 110 and server 120. Of course, this device can also be applied to other implementation environments and configured on mobile terminals in other implementation environments, or jointly configured on mobile terminals and servers; this embodiment does not impose limitations.

[0110] As shown in Figure 8, in an exemplary embodiment, the biometric-based biometric information processing device includes:

[0111] Detection module 810 is configured to detect instructions that indicate the activation of at least two cameras to collect biological information respectively;

[0112] The acquisition module 820 is configured to respond to an instruction to activate at least two cameras associated with the mobile terminal, so as to obtain images containing biological information captured by each camera respectively;

[0113] The processing module 830 is configured to send images containing biological information captured by each camera to the server so that the server can identify the biological information contained in each image, obtain at least two types of biological information, and associate the at least two types of biological information with the same user identifier.

[0114] In another exemplary embodiment, the device further includes:

[0115] The first generation module is configured to generate an instruction to enable at least two cameras to collect biological information when the registration entry on the bio-information registration interface displayed on the client is triggered.

[0116] The first jump module is configured to jump to and display the image preview interface, and to display the images captured by each camera on the image preview interface;

[0117] The registration module is configured to register at least two types of biological information based on the biological information feedback results returned by the server; the biological information feedback results are generated by the server based on the search results of at least two types of biological information in the registered database.

[0118] In another exemplary embodiment, the registration module is further configured to perform the following steps:

[0119] Display the bioinformatics feedback results returned by the server;

[0120] When an instruction to register based on at least two biometric information is detected, the client's login account identifier is sent to the server, so that the server associates at least two biometric information with the client's login account identifier and stores it in the registered database.

[0121] In another exemplary embodiment, the processing module 830 is further configured to perform the following steps:

[0122] Detect whether the client is currently logged into an account.

[0123] If not, the specified application associated with the client is invoked to log in on the client based on the account identifier logged in in the specified application.

[0124] In another exemplary embodiment, the device further includes:

[0125] The quality inspection module is configured to periodically check the image quality of the images captured in real time by each camera, and based on the image inspection results, display the image acquisition progress of each camera separately on the image preview interface.

[0126] In another exemplary embodiment, the device further includes:

[0127] The second generation module is configured to generate an instruction to enable at least two cameras to collect biological information when the verification entry on the biometric verification interface displayed on the client is triggered.

[0128] The second jump module is configured to jump to and display the image preview interface, and to display the images captured by each camera on the image preview interface;

[0129] The verification module is configured to display the biometric verification results returned by the server; when at least two types of biometric information match the registration information associated with the logged-in account identifier in the client, the biometric verification result indicates successful verification.

[0130] In another exemplary embodiment, the acquisition module 820 is further configured to perform the following steps:

[0131] Create at least two asynchronous view threads;

[0132] Each view thread is responsible for activating different cameras to acquire images from each camera; the view threads are run to obtain images containing biological information from each camera.

[0133] In another exemplary embodiment, at least two cameras are a front-facing camera and a rear-facing camera of the mobile terminal, respectively. The front-facing camera is used to capture images containing facial information, and the rear-facing camera is used to capture images containing palm print information.

[0134] In another exemplary embodiment, the mobile terminal has a front-facing camera and a rear-facing camera, and the mobile terminal is also connected to an external camera; at least two cameras include at least one of the front-facing camera and the rear-facing camera, and also include an external camera.

[0135] It should be noted that the apparatus and method provided in the above embodiments belong to the same concept, and the specific ways in which each module and unit performs operations have been described in detail in the method embodiments, and will not be repeated here. In practical applications, the biometric information processing apparatus based on biometrics provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above, and this is not a limitation here.

[0136] Embodiments of this application also provide an electronic device, including: one or more processors; and a memory for storing one or more computer programs, which, when executed by the one or more processors, cause the electronic device to implement the biometric-based bio-information processing method provided in the above embodiments.

[0137] Figure 9 shows a schematic diagram of a computer system suitable for implementing the electronic device of this application. It should be noted that the electronic device may be a mobile terminal or server 120 in the implementation environment shown in Figure 1, or a mobile terminal or server in other implementation environments; no limitation is imposed here. It should also be noted that the computer system 900 of the electronic device shown in Figure 9 is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0138] As shown in Figure 9, the computer system 900 includes a Central Processing Unit (CPU) 901, which can perform various appropriate actions and processes based on computer programs stored in Read-Only Memory (ROM) 902 or loaded from storage portion 908 into Random Access Memory (RAM) 903, such as performing the methods described in the above embodiments. The RAM 903 also stores various computer programs and data required for system operation. The CPU 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0139] The following components are connected to I / O interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to I / O interface 905 as needed. Removable media 99, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 910 as needed so that computer programs read from them can be installed into storage section 908 as needed.

[0140] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 99. When the computer program is executed by central processing unit (CPU) 901, it performs various functions defined in the system of this application.

[0141] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. Computer programs contained on computer-readable media can be transmitted using any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0143] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0144] Another aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor of an electronic device, implements the biometric-based biometric information processing method as described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0145] Another aspect of this application provides a computer program product comprising a computer program stored in a computer-readable storage medium. A processor of an electronic device reads the computer program from the computer-readable storage medium and executes the computer program, causing the electronic device to perform the biometric-based biometric information processing method provided in the various embodiments described above.

[0146] In summary, this application provides a biometric information processing method, apparatus, device, computer-readable storage medium, and computer program product. The client detects an instruction to activate at least two cameras to collect biometric information. Responding to this instruction, the client activates at least two cameras associated with the mobile terminal, acquiring images containing biometric information from each camera. These images are then sent to the server. The server identifies the biometric information contained in each image, obtaining at least two types of biometric information and associating them with the same user identifier. Technically, the simultaneous collection of different biometric information from multiple cameras utilizes the parallel processing capabilities of the mobile terminal's hardware resources, reducing the time overhead of biometric information collection and improving processing efficiency during the data acquisition phase. Simultaneously, the multi-dimensional collection of biometric information provides a richer and more accurate data foundation for subsequent server-side identification and association, reducing the probability of association errors caused by single biometric information recognition errors and improving the accuracy of associating biometric information with user identifiers.

[0147] Furthermore, when the registration entry on the biometric registration interface displayed on the client is triggered, the client generates an instruction to activate at least two cameras to collect biometric information separately. It then redirects to an image preview interface, displaying images from each camera simultaneously. Based on the biometric feedback returned by the server, at least two types of biometric information are registered. The image preview interface provides real-time visual feedback, allowing users to adjust their posture and position based on the preview images, optimizing the angle and state of biometric information collection. This helps improve the quality of the collected biometric images, reducing server-side recognition difficulties caused by poor image quality, thereby increasing the success rate and efficiency of biometric registration. Simultaneously, displaying images from each camera allows users to compare and adjust different biometric information collection situations, enhancing their control over the entire registration process.

[0148] Furthermore, the client displays the biometric feedback results returned by the server. When an instruction indicating registration based on at least two biometric identifiers is detected, the client sends its logged-in account identifier to the server, enabling the server to associate and store at least two biometric identifiers with the client's logged-in account identifier in the registered database. Clearly displaying the biometric feedback results provides users with explicit registration status information, allowing them to understand their registration status promptly and make appropriate decisions. Accurately associating and storing biometric information with account identifiers ensures the consistency and integrity of the correspondence between biometric information and user identifiers in the database, improving the accuracy and reliability of database management and facilitating subsequent information retrieval and verification operations.

[0149] Furthermore, when sending the client's login account identifier to the server, the client first checks if it is currently logged in with that account identifier. If not, it invokes the specified application associated with the client and logs in on the client based on the account identifier logged in within that application. This automatic detection and login invocation mechanism avoids the tedious process of users manually entering account information, reduces login failures due to manual input errors, and improves the success rate and efficiency of account login. Simultaneously, utilizing the account information already logged in with the specified application enables account information reuse, reduces data redundancy, and improves the utilization rate of system resources.

[0150] Furthermore, the client periodically checks the image quality of the images captured in real time by each camera, and displays the image acquisition progress of each camera separately on the image preview interface based on the image detection results. Periodic image quality checks can promptly identify image quality problems during acquisition, such as blurring or abnormal exposure, and dynamically adjust the acquisition strategy based on the detection results. Displaying the acquisition progress on the image preview interface allows users to intuitively understand the acquisition progress of each camera, rationally plan their adjustments and time, and improve the efficiency and quality of bioinformatics acquisition. At the same time, the display of acquisition progress also provides a reference for subsequent image selection, helping to filter out higher-quality bioinformatics images.

[0151] Furthermore, when the verification entry point on the biometric verification interface displayed on the client is triggered, the client generates an instruction to activate at least two cameras to collect biometric information. It then redirects to an image preview interface, displaying images collected by each camera, and shows the biometric verification results returned by the server. When at least two types of biometric information match the registration information associated with the logged-in account identifier in the client, the biometric verification result indicates successful verification. Using multiple cameras to collect various types of biometric information for verification increases the dimensionality and complexity of the verification process, improving its accuracy and security. Adjusting the acquisition status through the image preview interface ensures the quality of the collected biometric information, providing a reliable data foundation for accurate server-side verification. During the verification process, multiple types of biometric information corroborate each other, reducing verification errors caused by the forgery or misuse of a single biometric piece of information and enhancing the verification system's resistance to attacks.

[0152] Furthermore, when the client responds to a command to activate at least two cameras to acquire images containing biological information from each camera, at least two asynchronous view threads are created. Each view thread is responsible for activating different cameras to acquire images from each camera, and the view thread then obtains the image containing biological information. The use of asynchronous view threads enables parallel processing of image acquisition from each camera, fully utilizing the multi-core processing capabilities of the mobile terminal and improving image acquisition efficiency. Simultaneously, each thread operates independently; a malfunction in one camera will not affect image acquisition from other cameras, enhancing the stability and reliability of the image acquisition process and ensuring the integrity of the biological information acquisition.

[0153] Furthermore, at least two cameras are used: a front-facing camera and a rear-facing camera on the mobile terminal. The front-facing camera captures images containing facial information, while the rear-facing camera captures images containing palm print information. Utilizing the existing front and rear cameras of the mobile terminal for biometric data collection eliminates the need for additional hardware, reducing hardware costs and system complexity. Simultaneous collection of different biometric data by the front and rear cameras allows for the collection of multiple biometric data in a single operation, reducing collection time and user operation steps, and improving collection efficiency. Moreover, the different positions and viewing angles of the front and rear cameras enable the collection of biometric data from different angles, increasing the diversity and richness of the biometric data and improving the accuracy of server-side identification and verification.

[0154] Furthermore, the mobile terminal has a front-facing camera and a rear-facing camera, and is also connected to an external camera. At least two cameras are included, comprising at least one of the front-facing and rear-facing cameras, plus the external camera. The external camera typically has higher resolution and more professional acquisition capabilities, working in conjunction with the mobile terminal's built-in camera to provide higher-quality bio-information images. The flexible selection of different cameras based on different acquisition needs and scenarios improves the adaptability and flexibility of bio-information acquisition. Simultaneously, multi-camera combined acquisition increases the dimensionality and accuracy of bio-information, further enhancing the accuracy and security of bio-information identification and verification by the server.

[0155] Furthermore, the manual mentions that before the server-side identification of biometric information, the image containing biometric information undergoes preprocessing, such as color correction, denoising, and sharpening. Color correction adjusts the color distribution of the image to better match the requirements of human vision and the server-side identification algorithm, improving the recognizability of biometric information in the image. Denoising reduces noise interference in the image, making biometric features clearer, reducing the impact of noise on the server-side identification algorithm, and improving the accuracy of identification. Sharpening enhances the edges and details of the image, highlighting the features of biometric information, helping the server to extract biometric features more accurately, and improving the efficiency and accuracy of biometric identification.

[0156] After activating the cameras, the client acquires ambient light information from each camera and adjusts the camera parameters accordingly to ensure that the quality differences between images containing biometric information captured by different cameras meet preset requirements. By monitoring ambient light information in real time and adjusting camera parameters, the system can adapt to different lighting conditions, guaranteeing relatively consistent image quality from each camera. This avoids inconsistent image quality caused by variations in ambient light, reduces the likelihood of the server failing to accurately identify biometric information due to significant differences in image quality, and improves the stability and accuracy of biometric identification.

[0157] The client-side optimizes the camera's capture speed by adjusting at least one shooting parameter for each camera, such as frame rate, shutter speed, exposure time, and resolution, based on actual needs. Properly adjusting these shooting parameters allows for the capture of high-quality biometric images within the time it takes for the user to remain still. For example, increasing the frame rate increases the number of images captured per unit time, increasing the probability of obtaining clear biometric images; adjusting shutter speed, exposure time, and resolution according to ambient light and biometric recognition accuracy requirements optimizes image clarity and detail, improving the quality and efficiency of biometric data acquisition.

[0158] The biometric verification interface displays a reminder message, prompting users to ensure that the collected biometric information is their own. Liveness detection is introduced before or during image capture by the camera. This reminder enhances user awareness and reduces the possibility of unauthorized biometric information being collected due to user negligence or misoperation. Liveness detection technology verifies whether biometric information originates from a real biological individual, such as facial movement liveness detection and palm print blood flow detection. This effectively prevents the use of photos, videos, or other forged biometric information for verification, improving the security and reliability of biometric verification.

[0159] A single camera can capture at least two biometric data of the same type, such as simultaneously capturing palm prints from the left and right hands. This acquisition method increases the dimensionality and diversity of biometric information, providing more feature information for server-side identification and verification, and improving the accuracy and security of biometric identification. At the same time, it enhances the flexibility of the biometric identification scheme, enabling the system to adapt to different application scenarios and needs.

[0160] It is understood that in the specific embodiments of this application, data such as images containing biological information are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0161] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0162] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A biometric-based biometric information processing method, applied to a client running on a mobile terminal, the method comprising: The detection is used to instruct the activation of at least two cameras to collect biological information separately. In response to the instruction, at least two cameras associated with the mobile terminal are activated to obtain images containing biological information captured by each camera. and Images containing biological information captured by each camera are sent to the server so that the server can identify the biological information contained in each image, obtain at least two types of biological information, and associate the at least two types of biological information with the same user identifier.

2. The method according to claim 1, further comprising: When the registration entry on the bio-information registration interface displayed on the client is triggered, the instruction for instructing at least two cameras to collect bio-information is generated. The system will redirect to an image preview interface, where images captured by each camera will be displayed together. Based on the biological information feedback results returned by the server, the at least two types of biological information are registered; the biological information feedback results are generated by the server based on the search results of the at least two types of biological information in the registered database.

3. The method according to claim 2, wherein registering the at least two types of biological information based on the biological information feedback result returned by the server includes: Display the bio-information feedback results returned by the server; When an instruction to register based on the at least two biometric information is detected, the account identifier of the client login is sent to the server, so that the server associates the at least two biometric information with the account identifier of the client login in the registered database.

4. The method according to claim 3, wherein sending the account identifier of the client login to the server when an instruction for indicating registration based on the at least two biometric information is detected includes: Detect whether the client is currently logged into an account. If not, the specified application associated with the client is invoked to log in to the client based on the account identifier logged in in the specified application.

5. The method according to claim 3 or 4, further comprising: Periodically check the image quality of the images captured in real time by each camera; Based on the image detection results, the image acquisition progress of each camera is displayed separately on the image preview interface.

6. The method according to any one of claims 1 to 5, wherein the method further comprises: When the verification entry on the biometric verification interface displayed by the client is triggered, the instruction for instructing at least two cameras to collect biometric information is generated. The system will redirect to an image preview interface, where images captured by each camera will be displayed together. The biometric verification results returned by the server are displayed; when at least two types of biometric information match the registration information associated with the logged-in account identifier in the client, the biometric verification results indicate successful verification.

7. The method according to any one of claims 1 to 6, wherein responding to the instruction to activate at least two cameras to respectively acquire images containing biological information captured by each camera comprises: Create at least two asynchronous view threads; Each view thread is responsible for activating different cameras to acquire images from each camera. Run the view thread to obtain images containing biological information captured by each camera.

8. The method according to any one of claims 1-7, wherein the at least two cameras are a front camera and a rear camera of the mobile terminal, the front camera being used to capture an image containing facial information, and the rear camera being used to capture an image containing palm print information.

9. The method according to any one of claims 1-8, wherein the mobile terminal has a front-facing camera and a rear-facing camera, and the mobile terminal is also connected to an external camera; the at least two cameras include at least one of the front-facing camera and the rear-facing camera, and further include the external camera.

10. A biometric information processing device, the device comprising: The detection module is configured to detect commands that indicate the activation of at least two cameras to collect biological information. The acquisition module is configured to, in response to the instruction, activate at least two cameras associated with the mobile terminal to acquire images containing biological information captured by each camera. The processing module is configured to send images containing biological information captured by each camera to the server, so that the server can identify the biological information contained in each image, obtain at least two types of biological information, and associate the at least two types of biological information with the same user identifier.

11. An electronic device, comprising: One or more processors; A memory for storing one or more computer programs that, when executed by one or more processors, cause the electronic device to perform the method as described in any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor of an electronic device, causes the electronic device to perform the method of any one of claims 1-9.

13. A computer program product comprising a computer program that, when executed by a processor of an electronic device, implements the method as described in any one of claims 1-9.

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