A method, device, electronic device and storage medium for generating effective fingerprint image

Abstract

The present application relates to the field of image processing, and discloses a method for generating an effective fingerprint image, including: collecting multiple fingerprint images input by a user on a client, performing fingerprint segmentation on each fingerprint image using a fingerprint segmentation model, and obtaining multiple segmented fingerprint images; identifying the transmission priority of each segmented fingerprint image; transmitting each segmented fingerprint image to a remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server, and obtain an effective fingerprint image of the multiple segmented fingerprint images. In addition, the present application also provides an effective fingerprint image generation device, an electronic device, and a computer-readable storage medium. The present application can improve the efficiency of generating effective fingerprint images.

Description

Technical Field

[0001] The present application relates to the field of image processing, and in particular to a method, device, electronic device and computer-readable storage medium for generating an effective fingerprint image. Background Art

[0002] Fingerprint image generation refers to the process of entering the user's fingerprint information on a mobile terminal and / or PC. Fingerprint image recognition can usually be used in areas such as secure unlocking (such as unlocking a mobile phone screen) and secure payment (such as order transaction payment). With the continuous development of information technology and the continuous updating of user data, how to generate a fingerprint image that meets the server verification and comparison requirements based on the original collected fingerprint image, and efficient fingerprint generation becomes increasingly important.

[0003] At present, fingerprint image generation is usually achieved by collecting fingerprint images entered by users on mobile terminals and / or PCs, and transmitting the collected fingerprint images to servers for storage and processing. However, during the fingerprint image collection process, the mobile terminal and / or PC will collect multiple images. In order to improve the recognition accuracy, the collected fingerprint images have a higher clarity, so each image occupies a larger memory, resulting in a slower speed in the transmission of fingerprint images to the server, which in turn leads to a slower speed in the subsequent generation of valid fingerprint images, which in turn affects the efficiency of generating valid fingerprint images. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a method, device, electronic device and computer-readable storage medium for generating an effective fingerprint image, which can improve the efficiency of generating an effective fingerprint image.

[0005] In a first aspect, the present application provides a method for generating an effective fingerprint image, comprising:

[0006] Collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images;

[0007] Determining a transmission priority of each of the segmented fingerprint images;

[0008] Each of the segmented fingerprint images is transmitted to a remote server according to the transmission priority, so that the multiple segmented fingerprint images are spliced ​​by the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images.

[0009] It can be seen that the embodiment of the present application uses the fingerprint segmentation model to perform fingerprint segmentation on multiple fingerprint images input by the user on the client to obtain multiple segmented fingerprint images, which can obtain the effective fingerprint area of ​​the collected fingerprint image, reduce the amount of image data subsequently transmitted to the server, thereby improving the speed of subsequent effective fingerprint image generation and ensuring the efficiency of effective fingerprint image generation; secondly, the embodiment of the present application can determine the transmission order of each subsequent segmented fingerprint image by determining the transmission priority of each segmented fingerprint image, thereby reducing the amount of data when the subsequent segmented fingerprint images are spliced, and further improving the speed of effective fingerprint image generation; further, the present application transmits each segmented fingerprint image to the remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain the effective fingerprint image of the multiple segmented fingerprint images, and can identify the user fingerprint information of the user in the client, and realize the effective fingerprint image of the user in the client. Therefore, the effective fingerprint image generation method proposed in the embodiment of the present application can improve the efficiency of effective fingerprint image generation.

[0010] In a possible implementation manner of the first aspect, performing fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain a plurality of segmented fingerprint images includes:

[0011] Utilizing the region detection network in the fingerprint segmentation model to perform fingerprint image region detection and marking on each of the fingerprint images, to obtain a plurality of fingerprint region images;

[0012] Each of the fingerprint region images is segmented using the region segmentation network in the fingerprint segmentation model to obtain a plurality of segmented fingerprint images.

[0013] In a possible implementation manner of the first aspect, the step of performing segmentation fingerprint image detection on each of the fingerprint images using the region detection network in the fingerprint segmentation model to obtain a plurality of fingerprint region images includes:

[0014] Using the convolutional layer in the region detection network to extract image features from each of the fingerprint images, to obtain a plurality of feature images;

[0015] Performing dimensionality reduction processing on each of the feature images using a pooling layer in the region detection network to obtain a plurality of reduced-dimensionality feature images;

[0016] Calculating the detection result of each of the reduced-dimensional feature images using the activation function;

[0017] According to the detection result, the fingerprint region image of each fingerprint image is marked to obtain a plurality of fingerprint region images.

[0018] In a possible implementation manner of the first aspect, before segmenting each of the fingerprint region images using the region segmentation network in the fingerprint segmentation model, the method further includes:

[0019] Acquire a training image set, and input the training image set into a pre-built region segmentation network for training to obtain training values ​​of the training image set;

[0020] Calculating the loss value of the training value and the label corresponding to each training image in the training image set;

[0021] When the loss value is not less than a preset threshold, the hyperparameters of the pre-constructed region segmentation network are updated until the loss value is less than the preset threshold, thereby obtaining a region segmentation network.

[0022] In a possible implementation manner of the first aspect, determining the transmission priority of each segmented fingerprint image includes:

[0023] Acquiring the fingerprint contact position of each of the segmented fingerprint images, and detecting the fingerprint rolling direction and fingerprint rolling speed of each of the segmented fingerprint images;

[0024] Calculating the number of fingerprint pixels of each segmented fingerprint image according to the fingerprint contact position, fingerprint rolling direction and fingerprint rolling speed;

[0025] According to the number of fingerprint pixels, each of the segmented fingerprint images is sorted by transmission priority to obtain the transmission priority of each of the segmented fingerprint images.

[0026] In a possible implementation manner of the first aspect, transmitting each of the segmented fingerprint images to the remote server according to the transmission priority includes:

[0027] According to the transmission priority, obtaining the transmission order of each of the segmented fingerprint images;

[0028] According to the transmission sequence, each of the segmented fingerprint images is transmitted to the remote server using a socket.

[0029] In a possible implementation manner of the first aspect, the splicing the multiple segmented fingerprint images by the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images includes:

[0030] The segmented fingerprint image first transmitted to the remote server is used as the stitching center point, and the segmented fingerprint image subsequently transmitted to the remote server is used as the point to be stitched;

[0031] An image stitching tool is used to perform fingerprint stitching on the points to be stitched and the stitching center point to obtain a valid fingerprint image of the multiple segmented fingerprint images.

[0032] In a second aspect, the present application provides a device for generating a valid fingerprint image, the device comprising:

[0033] A fingerprint segmentation module is used to collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images;

[0034] A priority identification module, used to determine the transmission priority of each segmented fingerprint image;

[0035] The effective fingerprint image generation module is used to transmit each of the segmented fingerprint images to the remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain the effective fingerprint image of the multiple segmented fingerprint images.

[0036] In a third aspect, the present application provides an electronic device, including:

[0037] at least one processor; and a memory communicatively coupled to the at least one processor;

[0038] The memory stores a computer program executable by the at least one processor, so that the at least one processor can execute the method for generating a valid fingerprint image as described in any one of the first aspects above.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the method for generating a valid fingerprint image as described in any one of the first aspects above is implemented.

[0040] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1 A schematic diagram of a flow chart of a method for generating an effective fingerprint image provided in one embodiment of the present application;

[0044] Figure 2 A schematic diagram of a partial element image frame of a fingerprint in a method for generating an effective fingerprint image provided by an embodiment of the present application;

[0045] Figure 3 In one embodiment of this application Figure 1 A flowchart of one of the steps of a method for generating an effective fingerprint image is provided;

[0046] Figure 4 A schematic diagram of a module of a device for generating a valid fingerprint image provided by an embodiment of the present application;

[0047] Figure 5 A schematic diagram of the internal structure of an electronic device for implementing a method for generating an effective fingerprint image according to an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0049] See also Figure 1 FIG. 1 is a flow chart of a method for generating a valid fingerprint image according to an embodiment of the present application. Figure 1 The effective fingerprint image generation method described in , comprising:

[0050] S1. Collect multiple fingerprint images input by the user at the client, and use a fingerprint segmentation model to perform fingerprint segmentation on each of the fingerprint images to obtain multiple segmented fingerprint images.

[0051] In the embodiment of the present application, the client refers to a program corresponding to the server, which provides local services to customers, such as an APP program, and the fingerprint image refers to a picture containing the fingerprint of the user's finger. In one embodiment of the present application, the collection of the multiple fingerprint images is obtained by combining one or more of the following methods: Method 1, using a press fingerprint collection method; Method 2, using a rolling fingerprint collection method. Among them, the press fingerprint collection method refers to the method of user fingerprint entry, that is, guiding the user to enter the fingerprint in different areas of the client's page, such as fingerprint entry on the mobile phone screen, which can be done by guiding the user to enter the fingerprint in the center, left side, right side, top side, bottom side and other positions of the mobile phone screen. The rolling fingerprint collection method refers to shooting the user's rolling finger fingerprint by an image collector at a preset frequency. It should be noted that when shooting the user's rolling finger fingerprint by an image collector, the user's finger rolling direction (such as rolling from left to right in sequence) needs to be pre-set.

[0052] For example, see Figure 2 , which is a schematic diagram of an element image frame of a fingerprint in a fingerprint image generation method provided by the present application;

[0053] It should be understood that each fingerprint image collected will contain many fingerprint edge areas and blank areas. Therefore, the present application performs fingerprint segmentation on each of the fingerprint images by using a fingerprint segmentation model to identify the segmented fingerprint image of each of the fingerprint images, thereby reducing the data volume of each of the fingerprint images, improving the transmission speed of subsequent fingerprint images, and ensuring the efficiency of generating effective fingerprints. In an embodiment of the present application, the fingerprint segmentation model includes a region detection network and a region segmentation network. The region detection network is used to detect the segmented fingerprint image of each of the fingerprint images, and the region segmentation network is used to segment the detected segmented fingerprint image. Optionally, the region detection network can be constructed by the YOLOv3 algorithm, and the region segmentation network can be constructed by the Res34-Unet algorithm.

[0054] As an embodiment of the present application, see Figure 3 As shown, the fingerprint segmentation model is used to perform fingerprint segmentation on each of the fingerprint images to obtain multiple segmented fingerprint images, including:

[0055] S301, performing fingerprint image region detection and marking on each of the fingerprint images using the region detection network in the fingerprint segmentation model to obtain a plurality of fingerprint region images;

[0056] S302: Segment each of the fingerprint region images using the region segmentation network in the fingerprint segmentation model to obtain a plurality of segmented fingerprint images.

[0057] Further, as another optional embodiment of the present application, the method of using the region detection network in the fingerprint segmentation model to perform segmented fingerprint image detection on each of the fingerprint images to obtain multiple fingerprint region images includes: using the convolutional layer in the region detection network to extract image features of each of the fingerprint images to obtain multiple feature images; using the pooling layer in the region detection network to perform dimensionality reduction processing on each of the feature images to obtain multiple reduced-dimensionality feature images; using the activation function to calculate the detection result of each of the reduced-dimensionality feature images; and marking the fingerprint region image of each of the fingerprint images according to the detection result to obtain multiple fingerprint region images.

[0058] Among them, the image feature extraction can be achieved through the convolution kernel in the convolution layer, and the dimensionality reduction of the feature image can be achieved through the dimensionality reduction function of the pooling layer, such as the relu function. The detection result includes: x, y, height, width and category, etc., wherein x and y represent the center point of the reduced dimensionality feature image, and the category indicates whether the reduced dimensionality feature image is the target area, that is, category 0 indicates that it is not the target area, and category 1 indicates that the predicted area is the target area. Therefore, the embodiment of the present application marks the reduced dimensionality feature image with category 1 as the fingerprint area image.

[0059] Furthermore, in the embodiment of the present application, the activation function includes:

[0060]

[0061] Among them, s ′ represents the reduced dimension feature image after activation, and s represents the reduced dimension feature image.

[0062] Furthermore, as another optional embodiment of the present application, before using the region segmentation network in the fingerprint segmentation model to segment each of the fingerprint region images, it also includes: obtaining a training image set, inputting the training image set into a pre-constructed region segmentation network for training to obtain a training value of the training image set; calculating a loss value between the training value and the label corresponding to each training image in the training image set; when the loss value is not less than a preset threshold, updating the hyperparameters of the pre-constructed region segmentation network until the loss value is less than the preset threshold, thereby obtaining the region segmentation network.

[0063] Among them, the label refers to the real fingerprint area of ​​each training image in the training image set, which is used to compare with the training value to supervise the learning ability of the pre-built region segmentation network. The loss value can be calculated by a loss function, such as a cross entropy loss algorithm. The preset threshold can be set to 0.1 or set according to the actual business scenario. The update of the hyperparameter can be achieved by a gradient descent algorithm, such as a stochastic gradient descent algorithm.

[0064] In another embodiment of the present application, the fingerprint segmentation of the multiple fingerprint images can also be achieved by calculating the fingerprint pixels of the fingerprint image and / or identifying the fingerprint contact position. The fingerprint segmentation by fingerprint contact position refers to determining the fingerprint area by the contact position of the finger with the acquisition window; further, the fingerprint segmentation of the multiple fingerprint images is achieved by calculating the fingerprint pixels of the fingerprint image, including: calculating the fingerprint pixels of each fingerprint point in each of the fingerprint images, deleting the fingerprint points whose fingerprint pixels do not meet the preset conditions from the fingerprint image, so as to achieve fingerprint segmentation of each of the fingerprint images.

[0065] S2. Determine the transmission priority of each segmented fingerprint image.

[0066] It should be understood that in each of the segmented fingerprint images there will be images with more fingerprint data and images with less fingerprint data. Therefore, the embodiment of the present application identifies the transmission priority of each segmented fingerprint image to determine the transmission order of subsequent segmented fingerprint images, thereby reducing the amount of data when the subsequent segmented fingerprint images are spliced, and further improving the speed of generating effective fingerprint images.

[0067] As an embodiment of the present application, determining the transmission priority of each of the segmented fingerprint images includes: obtaining the fingerprint contact position of each of the segmented fingerprint images, and detecting the fingerprint rolling direction and fingerprint rolling speed of each of the segmented fingerprint images, calculating the number of fingerprint pixels of each of the segmented fingerprint images according to the fingerprint contact position, fingerprint rolling direction and fingerprint rolling speed, and sorting the transmission priority of each of the segmented fingerprint images according to the number of fingerprint pixels to obtain the transmission priority of each of the segmented fingerprint images.

[0068] Among them, the fingerprint contact position refers to the contact area between the user's finger and the client screen when collecting the fingerprint image, the fingerprint rolling direction refers to the collection direction and collection speed when collecting the fingerprint image, and the number of fingerprint pixels is used to characterize the effective fingerprint area of ​​each of the segmented fingerprint images, that is, the more the number of fingerprint pixels, the larger the effective fingerprint area of ​​the segmented fingerprint image. Therefore, the embodiment of the present application ranks the transmission priority of the segmented fingerprint image with the largest number of fingerprint pixels in the highest position, and ranks the transmission priority of the segmented fingerprint image with the least number of fingerprint pixels in the lowest position.

[0069] S3. Transmit each of the segmented fingerprint images to a remote server according to the transmission priority, so that the remote server can splice the multiple segmented fingerprint images to obtain a valid fingerprint image of the multiple segmented fingerprint images.

[0070] In an embodiment of the present application, the remote server refers to a remote device corresponding to the client, which is used to manage and calculate the resources transmitted by the client, such as a web server, a file server, and a database server. In an embodiment of the present application, the remote server is used to store and manage the segmented fingerprint images transmitted by the client to achieve the splicing of the segmented fingerprint images and obtain the valid fingerprint image generation result of the segmented fingerprint images.

[0071] As an embodiment of the present application, transmitting each of the segmented fingerprint images to the remote server according to the transmission priority includes: obtaining the transmission order of each of the segmented fingerprint images according to the transmission priority, and transmitting each of the segmented fingerprint images to the remote server using a socket according to the transmission order.

[0072] Among them, the transmission order refers to the priority transmission of the segmented fingerprint image with a higher transmission priority, that is, the image containing the most fingerprint pixels in the segmented fingerprint image is transmitted to the remote server first, so as to reduce the subsequent splicing amount of the segmented fingerprint image by the remote server and improve the splicing speed of the segmented fingerprint image. The socket refers to the endpoint for two-way communication (i.e., client-server) between application processes on different hosts in the network. It can be generally understood that a socket is one end of process communication on the network.

[0073] Furthermore, in the embodiment of the present application, the multiple segmented fingerprint images are spliced ​​by the remote server to obtain all the fingerprint pixels of the multiple segmented fingerprint images, thereby obtaining the valid fingerprint images of the users corresponding to the multiple segmented fingerprint images. Optionally, the multiple segmented fingerprint images are spliced ​​by the remote server to obtain the valid fingerprint images of the multiple segmented fingerprint images, including: taking the segmented fingerprint image first transmitted to the remote server as the splicing center point, and taking the segmented fingerprint image subsequently transmitted to the remote server as the point to be spliced, and using an image splicing tool to perform fingerprint splicing on the point to be spliced ​​and the splicing center point to obtain the valid fingerprint image of the multiple segmented fingerprint images.

[0074] Optionally, the image stitching tool may be compiled using Java language.

[0075] Based on the generation of the valid fingerprint image, the user fingerprint information of the user at the client can be identified, which can be used for user identity identification of the client to ensure the safe use of the client by the user.

[0076] It can be seen that the embodiment of the present application uses the fingerprint segmentation model to perform fingerprint segmentation on multiple fingerprint images input by the user on the client to obtain multiple segmented fingerprint images, which can obtain the effective fingerprint area of ​​the collected fingerprint image, reduce the amount of image data subsequently transmitted to the server, thereby improving the speed of subsequent effective fingerprint image generation and ensuring the efficiency of effective fingerprint image generation; secondly, the embodiment of the present application can determine the transmission order of each subsequent segmented fingerprint image by determining the transmission priority of each segmented fingerprint image, thereby reducing the amount of data when the subsequent segmented fingerprint images are spliced, and further improving the speed of effective fingerprint image generation; further, the present application transmits each segmented fingerprint image to the remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain the effective fingerprint image of the multiple segmented fingerprint images, and can identify the user fingerprint information of the user in the client, so as to realize the generation of effective fingerprint images of the user in the client. Therefore, a method for generating an effective fingerprint image proposed in the embodiment of the present application can improve the efficiency of generating effective fingerprint images.

[0077] like Figure 4 FIG. 1 is a schematic diagram of a module of a device for generating an effective fingerprint image according to an embodiment of the present application.

[0078] The effective fingerprint image generating device 400 described in the present application can be installed in an electronic device. According to the functions to be implemented, the effective fingerprint image generating device may include a fingerprint segmentation module 401, a priority identification module 402 and an effective fingerprint image generating module 403. The module described in the present invention may also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0079] In this embodiment, the functions of each module / unit are as follows:

[0080] The fingerprint segmentation module 401 is used to collect multiple fingerprint images input by the user at the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images;

[0081] The priority identification module 402 is used to determine the transmission priority of each segmented fingerprint image;

[0082] The effective fingerprint image generating module 403 is used to transmit each of the segmented fingerprint images to the remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain the effective fingerprint image of the multiple segmented fingerprint images.

[0083] In detail, each module in the effective fingerprint image generating device 400 described in the embodiment of the present application adopts the same method as above when used. Figures 1 to 3 The effective fingerprint image generation method described in the invention has the same technical means and can produce the same technical effect, so it will not be repeated here.

[0084] like Figure 5 FIG. 1 is a schematic diagram of the internal structure of an electronic device for implementing a method for generating an effective fingerprint image according to an embodiment of the present application.

[0085] The electronic device may include a processor 50, a memory 51, a communication bus 52 and a communication interface 53, and may also include a computer program stored in the memory 51 and executable on the processor 50, such as a valid fingerprint image generation program.

[0086] In some embodiments, the processor 50 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 50 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions and processes data of the electronic device by running or executing programs or modules stored in the memory 51 (for example, executing a valid fingerprint image generation program, etc.), and calling data stored in the memory 51.

[0087] The memory 51 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 51 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 51 can also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 51 can also include both an internal storage unit of the electronic device and an external storage device. The memory 51 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the effective fingerprint image generation program, but also can be used to temporarily store data that has been calculated or is to be calculated.

[0088] The communication bus 52 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 51 and at least one processor 50, etc.

[0089] The communication interface 53 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0090] Figure 5 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 5 The structure shown does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0091] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 50 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0092] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0093] The effective fingerprint image generation program stored in the memory 51 of the electronic device 5 is a combination of multiple computer programs. When running in the processor 50, it can achieve:

[0094] Collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images;

[0095] Determining a transmission priority of each of the segmented fingerprint images;

[0096] Each of the segmented fingerprint images is transmitted to a remote server according to the transmission priority, so that the multiple segmented fingerprint images are spliced ​​by the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images.

[0097] Specifically, the specific implementation method of the processor 50 for the above computer program can refer to Figure 1 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0098] Furthermore, if the module / unit integrated in the electronic device 5 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0099] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0100] Collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images;

[0101] Determining a transmission priority of each of the segmented fingerprint images;

[0102] Each of the segmented fingerprint images is transmitted to a remote server according to the transmission priority, so that the multiple segmented fingerprint images are spliced ​​by the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0104] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0105] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0106] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or essential features of the present application.

[0107] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present application is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present application. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0108] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0109] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A method for generating an effective fingerprint image, characterized in that: The method comprises: Collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images; Determining a transmission priority of each of the segmented fingerprint images; Transmitting each of the segmented fingerprint images to a remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images; Wherein, determining the transmission priority of each segmented fingerprint image includes: Acquiring the fingerprint contact position of each of the segmented fingerprint images, and detecting the fingerprint rolling direction and fingerprint rolling speed of each of the segmented fingerprint images; Calculating the number of fingerprint pixels of each segmented fingerprint image according to the fingerprint contact position, fingerprint rolling direction and fingerprint rolling speed; According to the number of fingerprint pixels, each of the segmented fingerprint images is sorted by transmission priority to obtain the transmission priority of each segmented fingerprint image; wherein the transmission priority of the segmented fingerprint image with the largest number of fingerprint pixels is ranked highest, and the transmission priority of the segmented fingerprint image with the smallest number of fingerprint pixels is ranked lowest.

2. The effective fingerprint image generation method according to claim 1, characterized in that: The method of performing fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain a plurality of segmented fingerprint images includes: Utilizing the region detection network in the fingerprint segmentation model to perform fingerprint image region detection and marking on each of the fingerprint images, to obtain a plurality of fingerprint region images; Each of the fingerprint region images is segmented using the region segmentation network in the fingerprint segmentation model to obtain a plurality of segmented fingerprint images.

3. The effective fingerprint image generation method according to claim 2, characterized in that: The method of using the region detection network in the fingerprint segmentation model to perform fingerprint image region detection and marking on each fingerprint image to obtain multiple fingerprint region images includes: Using the convolutional layer in the region detection network to extract image features from each of the fingerprint images, to obtain a plurality of feature images; Performing dimensionality reduction processing on each of the feature images using a pooling layer in the region detection network to obtain a plurality of reduced-dimensionality feature images; Calculating the detection result of each of the reduced-dimensional feature images using an activation function; According to the detection result, the fingerprint region image of each fingerprint image is marked to obtain a plurality of fingerprint region images.

4. The effective fingerprint image generation method according to claim 2, characterized in that: Before segmenting each of the fingerprint region images using the region segmentation network in the fingerprint segmentation model, the method further includes: Acquire a training image set, and input the training image set into a pre-built region segmentation network for training to obtain training values ​​of the training image set; Calculating the loss value of the training value and the label corresponding to each training image in the training image set; When the loss value is not less than a preset threshold, the hyperparameters of the pre-constructed region segmentation network are updated until the loss value is less than the preset threshold, thereby obtaining a region segmentation network.

5. The effective fingerprint image generation method according to claim 1, characterized in that: The step of transmitting each of the segmented fingerprint images to a remote server according to the transmission priority includes: According to the transmission priority, obtaining the transmission order of each of the segmented fingerprint images; According to the transmission sequence, each of the segmented fingerprint images is transmitted to the remote server using a socket.

6. The effective fingerprint image generation method according to claim 1, characterized in that: The step of splicing the multiple segmented fingerprint images through the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images includes: The segmented fingerprint image first transmitted to the remote server is used as the stitching center point, and the segmented fingerprint image subsequently transmitted to the remote server is used as the point to be stitched; An image stitching tool is used to perform fingerprint stitching on the points to be stitched and the stitching center point to obtain a valid fingerprint image of the multiple segmented fingerprint images.

7. A device for generating an effective fingerprint image, characterized in that: The device comprises: A fingerprint segmentation module is used to collect multiple fingerprint images input by the user on the client, and perform fingerprint segmentation on each of the fingerprint images using a fingerprint segmentation model to obtain multiple segmented fingerprint images; A priority identification module, used to determine the transmission priority of each segmented fingerprint image; A valid fingerprint image generating module, used for transmitting each of the segmented fingerprint images to a remote server according to the transmission priority, so as to splice the multiple segmented fingerprint images through the remote server to obtain a valid fingerprint image of the multiple segmented fingerprint images; Wherein, determining the transmission priority of each segmented fingerprint image includes: Acquiring the fingerprint contact position of each of the segmented fingerprint images, and detecting the fingerprint rolling direction and fingerprint rolling speed of each of the segmented fingerprint images; Calculating the number of fingerprint pixels of each segmented fingerprint image according to the fingerprint contact position, fingerprint rolling direction and fingerprint rolling speed; According to the number of fingerprint pixels, each of the segmented fingerprint images is sorted by transmission priority to obtain the transmission priority of each segmented fingerprint image; wherein the transmission priority of the segmented fingerprint image with the largest number of fingerprint pixels is ranked highest, and the transmission priority of the segmented fingerprint image with the smallest number of fingerprint pixels is ranked lowest.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so as to enable the at least one processor to perform the method for generating a valid fingerprint image according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating a valid fingerprint image according to any one of claims 1 to 6 is implemented.

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