A recognition method and device based on fusion of touch and fingerprint sensors

Abstract

The present application relates to the technical field of biometric identification, and particularly relates to a recognition method and device based on fusion of touch and fingerprint sensors, equipment and storage medium, wherein the method comprises: acquiring a user finger information image; acquiring a finger posture and a confidence level based on the finger information image; extracting features of the finger information image, generating a feature template by using the features of the finger information image, the finger posture and the confidence level, and storing the feature template in correspondence with an identity; when a user uses, acquiring finger information of the user, comparing the finger information with the feature template, and completing identity recognition. By combining the fuzzy outline of the finger obtained by the touch sensor and the local clear ridge line texture obtained by the fingerprint sensor, higher-precision finger posture estimation is realized at a lower cost, higher-precision fingerprint recognition performance is realized, the posture when the finger is pressed is introduced as additional constraint information, higher-precision identity recognition is realized, and use safety is improved.

Description

Technical Field

[0001] This application relates to the field of biometric identification technology, and in particular to an identification method, apparatus, device and storage medium based on the fusion of touch and fingerprint sensors. Background Technology

[0002] Currently, the mainstream authentication schemes for identity recognition modules based on small fingerprint acquisition devices (especially those included in mobile devices such as smartphones) rely on partial fingerprint images for identification. Because these fingerprint sensors have a limited acquisition area, they can only capture a small portion of the fingerprint. Different fingerprints are more likely to produce highly similar local patterns, meaning the probability of false matches is relatively high. This is especially true since many fingerprint recognition systems require the ability to match fingerprints under arbitrary rotation and translation, which further exacerbates the problem. Therefore, new solutions are particularly needed to reduce the probability of false matches.

[0003] Touch sensors are input sensors in smartphones and other smart devices, used to detect the coordinates of finger touch points. Researchers have proposed schemes to measure finger posture from touch signals, increasing the amount of input information. However, touch sensors have not yet been used for fingerprint identification. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application is to propose an identification method based on the fusion of touch and fingerprint sensors to solve the problem of false information matching that easily occurs in existing technologies.

[0006] The second objective of this application is to provide an apparatus.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a computer-readable storage medium.

[0009] To achieve the above objectives, the first aspect of this application proposes a recognition method based on the fusion of touch and fingerprint sensors, comprising:

[0010] Acquire an image of the user's finger;

[0011] Finger posture and confidence level are obtained based on the finger information image;

[0012] Extract features from the finger information image, generate feature templates using the features of the finger information image, the finger posture, and the confidence level, and establish a correspondence between the feature templates and the identity and store them;

[0013] When a user uses the device, the device acquires the user's finger information and compares the finger information with the feature template to complete the identity verification.

[0014] Preferably, acquiring the user's finger information image includes:

[0015] Acquire the contour image of the user's finger when it comes into contact with the touch screen and the fingerprint image of the user's finger when it comes into contact with the fingerprint collection area;

[0016] This includes capturing images in a single, fixed posture, capturing images multiple times in different postures, and capturing images continuously in sequence during finger sliding or scrolling.

[0017] Preferably, obtaining the finger pose and confidence level based on the finger information image includes: obtaining the finger pose and confidence level using at least one of the contour image and the fingerprint image.

[0018] Preferably, the method further includes: when using the contour image and the fingerprint image simultaneously to obtain finger posture and confidence, first using the contour image to initially obtain posture information, and then using the fingerprint image information to adjust the posture information.

[0019] Preferably, obtaining the attitude information includes: obtaining the attitude information using supervised learning methods or empirical formulas.

[0020] Preferably, the step of acquiring the user's finger information when the user uses the device, and comparing the finger information with the feature template to complete identity recognition includes:

[0021] For a newly entered fingerprint, based on its pose information, the registered fingerprint database retrieves the registration data with the closest absolute pose as a sub-database and compares them. The final score is calculated by comprehensively considering the image comparison score, pose similarity, and confidence level to perform identity verification and complete identity recognition.

[0022] Preferably, the step of comparing the finger information with the feature template further includes:

[0023] For each fingerprint, the fingerprint image is geometrically transformed according to its pose to correct its position and rotation angle, then features are extracted and subsequent matching is performed.

[0024] For each fingerprint, the pose is fused with the original image features as an additional feature and then used for subsequent matching;

[0025] The fingerprint matching search space is reduced by using posture information, and only the nearest registered fingerprint is matched.

[0026] To achieve the above objectives, a second aspect of this application provides an identification device based on the fusion of touch and fingerprint sensors, comprising:

[0027] The image acquisition module acquires images of the user's finger information;

[0028] The posture acquisition module acquires the finger posture and confidence level based on the finger information image;

[0029] The feature extraction module extracts features from the finger information image, generates a feature template using the features of the finger information image, the finger posture, and the confidence level, and establishes a correspondence between the feature template and the identity and stores it.

[0030] The recognition module acquires the user's finger information when the user uses the device, compares the finger information with the feature template, and completes the identity recognition.

[0031] To achieve the above objectives, a third aspect of this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0032] The memory stores computer-executed instructions;

[0033] The processor executes computer execution instructions stored in the memory to implement the method described in any of the preceding descriptions.

[0034] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium, comprising computer-executable instructions stored therein, which, when executed by a processor, are used to implement the method described in any of the above embodiments.

[0035] This application provides an identification method based on the fusion of touch and fingerprint sensors. By combining the blurred outline of the finger obtained by the touch sensor with the locally clear ridge texture obtained by the fingerprint sensor, it achieves high-precision finger pose estimation at a low cost, thereby assisting in achieving high-precision fingerprint recognition performance. The finger pose during pressing is introduced as additional constraint information, thereby achieving higher-precision identity recognition and improving security.

[0036] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0037] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0038] Figure 1A flowchart illustrating a first specific embodiment of an identification method based on the fusion of touch and fingerprint sensors provided by the present invention;

[0039] Figure 2 This is a flowchart of a recognition method based on the fusion of touch and fingerprint sensors.

[0040] Figure 3 This is a schematic diagram of the sensor image acquisition process;

[0041] Figure 4 This is a schematic diagram for posture-assisted recognition.

[0042] Figure 5 This is a structural block diagram of a recognition device based on the fusion of touch and fingerprint sensors, provided in an embodiment of the present invention. Detailed Implementation

[0043] The core of this invention is to provide an identification method, device, electronic device, and storage medium based on the fusion of touch and fingerprint sensors. By introducing the posture of the finger when pressing as additional constraint information, higher accuracy of identity recognition is achieved, thereby improving the security of use.

[0044] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] Please refer to Figure 1 , Figure 1 The flowchart illustrates a first specific embodiment of a recognition method based on the fusion of touch and fingerprint sensors provided by the present invention; the specific operation steps are as follows:

[0046] Step S101: Acquire an image of the user's finger information;

[0047] The acquisition of the user's finger information image includes:

[0048] Acquire the contour image of the user's finger when it comes into contact with the touch screen and the fingerprint image of the user's finger when it comes into contact with the fingerprint collection area;

[0049] This includes capturing images in a single, fixed posture, capturing images multiple times in different postures, and capturing images continuously in sequence during finger sliding or scrolling.

[0050] Step S102: Obtain finger posture and confidence level based on the finger information image;

[0051] Finger pose and confidence level are obtained using at least one of the contour image and the fingerprint image;

[0052] When the contour image and the fingerprint image are used simultaneously to obtain finger posture and confidence, the posture information is first obtained by using the contour image, and then the posture information is adjusted by using the fingerprint image information.

[0053] The acquisition of attitude information includes: acquiring attitude information using supervised learning methods or empirical formulas.

[0054] Step S103: Extract the features of the finger information image, generate a feature template using the features of the finger information image, the finger posture and the confidence level, and establish a correspondence between the feature template and the identity and store it;

[0055] Step S104: When the user uses the device, obtain the user's finger information, compare the finger information with the feature template, and complete the identity recognition.

[0056] For a newly entered fingerprint, based on its pose information, the registered fingerprint database retrieves the registration data with the closest absolute pose as a sub-database and compares them. The final score is calculated by comprehensively considering the image comparison score, pose similarity, and confidence level to perform identity verification and complete identity recognition.

[0057] Before comparing the finger information with the feature template, the process also includes:

[0058] For each fingerprint, the fingerprint image is geometrically transformed according to its pose to correct its position and rotation angle, then features are extracted and subsequent matching is performed.

[0059] For each fingerprint, the pose is fused with the original image features as an additional feature and then used for subsequent matching;

[0060] The fingerprint matching search space is reduced by using posture information, and only the nearest registered fingerprint is matched.

[0061] This embodiment provides an identification method based on the fusion of touch and fingerprint sensors. By combining the blurred outline of the finger obtained by the touch sensor with the locally clear ridge texture obtained by the fingerprint sensor, it achieves high-precision finger posture estimation at a low cost, thereby assisting in achieving high-precision fingerprint recognition performance. The posture of the finger when pressing is introduced as additional constraint information, thereby achieving higher-precision identity recognition and improving security.

[0062] Based on the above embodiments, this embodiment describes a recognition method based on the fusion of touch and fingerprint sensors, as follows: Figure 2 As shown, the details are as follows:

[0063] This embodiment provides an identity recognition method based on the fusion of touch and fingerprint sensors. It jointly estimates finger pose (note that the finger pose in this invention includes the lateral and longitudinal coordinates of the finger center, as well as the finger direction) and confidence level by combining finger contour information collected by the touch sensor and local fingerprint information collected by the fingerprint sensor. Furthermore, it uses pose information to assist fingerprint recognition, reducing the probability of false matches and improving the accuracy of the identity recognition algorithm. The method includes:

[0064] Registration phase:

[0065] like Figure 3 As shown, the touch image acquisition module and the fingerprint image acquisition module simultaneously acquire touch and fingerprint images of the registered finger (including but not limited to images acquired in a single fixed posture, images acquired multiple times in different postures, and images acquired continuously in sequence during the finger sliding or rolling process).

[0066] The registration module extracts features from touch and fingerprint images (features used for pose estimation or identity recognition) and generates corresponding templates, which are then stored in the system. The features extracted during this registration process include, but are not limited to, pose, minutiae, orientation fields, ridge features, and various texture features.

[0067] The registration module stores all fingerprint templates of the registered fingers and establishes a correspondence between image features and identity.

[0068] Both fingerprint registration and recognition stages utilize a pose estimation module. The pose estimation methods used in these two stages can be the same or different.

[0069] When a user's finger comes into contact with the sensor's acquisition surface, the touch image acquisition module and the fingerprint image acquisition module acquire the current touch and fingerprint images, respectively.

[0070] The pose estimation module uses touch and fingerprint images to estimate the current finger pose and the confidence level of the estimation result. Inputs to this process include, but are not limited to: using only touch image information; using only fingerprint image information; using both touch and fingerprint image information; initially estimating the pose using the touch image and then further refining it using fingerprint image information. Pose estimation methods can employ supervised learning-based methods to regress finger pose information and confidence levels, or they can use empirical formulas or other estimation schemes.

[0071] The output of this pose estimation process is passed to the registration module or the identity recognition module.

[0072] The identity recognition module in this embodiment uses finger pose and estimated confidence level as auxiliary information to further constrain the matching of local fingerprints. An example of pose-assisted recognition is shown below. Figure 4As shown, the registered fingerprint database contains a series of registered fingerprints and pose information, where x, y, θ, and p represent the horizontal and vertical coordinates of the center of the corresponding fingerprint estimate, the rotation angle, and the confidence level, respectively. For a newly input fingerprint, based on its pose information, registered data with absolutely similar poses are retrieved from the registered fingerprint database as a sub-database for comparison. The final score is calculated by comprehensively considering the image comparison score, the degree of pose similarity, and the confidence level of the pose estimation. This method can constrain image texture information while adding auxiliary judgment on pose rationality, thereby increasing recognition accuracy.

[0073] Another way to use gestures is for the recognition module to prompt the user to input a fingerprint in a specific gesture. If the user's input fingerprint gesture does not meet the requirements, verification will not proceed. As needed, the system can also require the user to provide fingerprints in multiple gestures sequentially. Only when fingerprints from all gestures are matched will authentication be successful, thus improving security.

[0074] Pose orientation can assist matching algorithms in ways including but not limited to:

[0075] For each input fingerprint, the fingerprint image is geometrically transformed according to its pose to correct its position and rotation angle, then features are extracted and subsequent matching is performed;

[0076] For each fingerprint, the pose is fused with the original image features as an additional feature and used for subsequent matching;

[0077] Reduce the search space for fingerprint matching by using pose information, and only match with registered fingerprints that are close to each other (one feasible way to determine this is that, based on the pose estimation results, the Euclidean distance between the centers of the two fingerprint images is less than a certain fixed value);

[0078] First, a conventional fingerprint matching algorithm is used. After obtaining preliminary matching and relative pose estimation results, the consistency between the estimated absolute pose and relative pose between the two fingerprints is considered, and then the matching results are adjusted.

[0079] During the matching phase, any possible fingerprint matching algorithm can be used as the base matching scheme and combined with finger pose information. Furthermore, the differences in discrimination ability between different fingerprint regions can be considered during the matching phase to adjust the results. For example, the central region of the finger usually has more detail points and a more complex texture, so its calculation result can be given a slightly higher weight than that of the lateral regions of the finger.

[0080] It should be noted that the identity recognition algorithm proposed in this embodiment not only constrains the similarity of fingerprint image textures, but also constrains the fingerprint pose. Therefore, it is theoretically more reliable than existing algorithms that rely solely on image texture matching (for example, the fingerprint on the left side of a finger cannot match the fingerprint on the right side of a finger, even though their textures may be very similar).

[0081] This invention provides an identification method based on the fusion of touch and fingerprint sensors. The method estimates finger posture by jointly using finger contour information collected by the touch sensor and local fingerprint information collected by the fingerprint sensor. The finger posture in this embodiment includes the horizontal and vertical coordinates of the finger center, as well as the finger direction and confidence level. Furthermore, the posture information is used to assist fingerprint recognition, reduce the probability of false matches, and improve the accuracy of the identity recognition algorithm.

[0082] Based on the above embodiments, this embodiment describes the recognition process as follows:

[0083] User input is processed through touch and fingerprint image acquisition modules to obtain corresponding image information;

[0084] If this is the user registration stage, the image information will be processed by the subsequent dotted path registration module to extract the required features and save it as a registration template;

[0085] If this is the algorithm recognition stage, the image information and registration template are input into the pose estimation and identity recognition module, which outputs the estimated finger pose and the identified identity (if the identity is in the registration template library, the corresponding registered identity is returned; otherwise, the result is returned that the identity is not in the library). Note that the two modules can be executed independently, or one can pass auxiliary information to the other, or the two modules can exchange information to obtain more accurate prediction results;

[0086] Output the identified identity for subsequent identity verification applications.

[0087] Please refer to Figure 5 , Figure 5 A structural block diagram of a recognition device based on the fusion of touch and fingerprint sensors is provided for an embodiment of the present invention; the specific device may include:

[0088] Image acquisition module 100 acquires an image of the user's finger information;

[0089] The posture acquisition module 200 acquires the finger posture and confidence level based on the finger information image;

[0090] The feature extraction module 300 extracts features from the finger information image, generates a feature template using the features of the finger information image, the finger posture, and the confidence level, and establishes a correspondence between the feature template and the identity and stores it.

[0091] The recognition module 400 acquires the user's finger information when the user uses it, compares the finger information with the feature template, and completes the identity recognition.

[0092] This embodiment provides an identification device based on the fusion of touch and fingerprint sensors to implement the aforementioned identification method based on the fusion of touch and fingerprint sensors. Therefore, the specific implementation of the identification device based on the fusion of touch and fingerprint sensors can be found in the embodiment section of the identification method based on the fusion of touch and fingerprint sensors mentioned above. For example, the image acquisition module 100, the posture acquisition module 200, the feature extraction module 300, and the identification module 400 are respectively used to implement steps S101, S102, S103, and S104 in the aforementioned identification method based on the fusion of touch and fingerprint sensors. Therefore, the specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.

[0093] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0094] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0095] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0096] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0097] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0098] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0099] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0101] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0102] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0103] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0104] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0105] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0106] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A recognition method based on the fusion of touch and fingerprint sensors, characterized in that, include: Acquiring user finger information images includes: acquiring the contour image of the user's finger when it is in contact with the touch screen and the fingerprint image of the user's finger when it is in contact with the fingerprint collection area; including single acquisition of images under a fixed usage posture, multiple acquisition of images under different postures, and continuous acquisition of images during finger sliding or rolling in sequence. Obtaining finger posture and confidence based on the finger information image includes: using the contour image and the fingerprint image to obtain finger posture and confidence; when using the contour image and the fingerprint image simultaneously to obtain finger posture and confidence, first use the contour image to initially obtain posture information, and then use the fingerprint image information to adjust the posture information. Extract features from the finger information image, generate feature templates using the features of the finger information image, the finger posture, and the confidence level, and establish a correspondence between the feature templates and the identity and store them; When a user uses the device, the device acquires the user's finger information and compares the finger information with the feature template to complete the identity verification.

2. The identification method based on the fusion of touch and fingerprint sensors according to claim 1, characterized in that, The acquisition of attitude information includes: acquiring attitude information using supervised learning methods or empirical formulas.

3. The identification method based on the fusion of touch and fingerprint sensors according to claim 1, characterized in that, The step of acquiring the user's finger information when the user uses the device, comparing the finger information with the feature template, and completing the identity verification includes: For a newly entered fingerprint, based on its pose information, the registered fingerprint database retrieves the registration data with the closest absolute pose as a sub-database and compares them. The final score is calculated by comprehensively considering the image comparison score, pose similarity, and confidence level to perform identity verification and complete identity recognition.

4. The identification method based on the fusion of touch and fingerprint sensors according to claim 3, characterized in that, Before comparing the finger information with the feature template, the process also includes: For each fingerprint, the fingerprint image is geometrically transformed according to its pose to correct its position and rotation angle, then features are extracted and subsequent matching is performed. For each fingerprint, the pose is fused with the original image features as an additional feature and then used for subsequent matching; The fingerprint matching search space is reduced by using posture information, and only the nearest registered fingerprint is matched.

5. A recognition device based on the fusion of touch and fingerprint sensors, employing the recognition method based on the fusion of touch and fingerprint sensors according to any one of claims 1-4, characterized in that, include: The image acquisition module acquires images of the user's finger information; The posture acquisition module acquires the finger posture and confidence level based on the finger information image; The feature extraction module extracts features from the finger information image, generates a feature template using the features of the finger information image, the finger posture, and the confidence level, and establishes a correspondence between the feature template and the identity and stores it. The recognition module acquires the user's finger information when the user uses the device, compares the finger information with the feature template, and completes the identity recognition.

6. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-4.

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