Fingerprint identification component, method, device, terminal and storage medium

Abstract

This disclosure relates to a fingerprint recognition component, method, apparatus, terminal, and storage medium. The fingerprint recognition component includes an optical lens array, which includes at least one non-uniform lens having at least two curvatures. The fingerprint recognition component acquires a 3D fingerprint image (e.g., a finger's fingerprint) that differs from the acquired 2D fake fingerprint image (e.g., a fingerprint photograph), thereby better preventing 2D fake fingerprints and improving security.

Description

Technical Field

[0001] This disclosure relates to the field of terminal technology, and in particular to a fingerprint recognition component, method, device, terminal and storage medium. Background Technology

[0002] Currently, more and more mobile phones and other terminals are equipped with fingerprint unlocking function, which is generally implemented through fingerprint recognition components.

[0003] For example, when a user unlocks their phone with their fingerprint, the screen illuminates the finger, and the ridges of the fingerprint reflect light of varying intensities to the fingerprint sensor component, which then captures the fingerprint image.

[0004] However, fingerprint recognition sensor components are limited to black and white grayscale levels. They only sense and collect grayscale intensity values ​​and cannot distinguish three-dimensional structures such as ridges and valleys, thus failing to identify fake fingerprints with printed planar structures. Therefore, they are not effective against 2D fake fingerprints. Summary of the Invention

[0005] To overcome the problems existing in related technologies, this disclosure provides a fingerprint recognition component, method, device, terminal and storage medium.

[0006] According to a first aspect of the present disclosure, a fingerprint recognition component is provided, the fingerprint recognition component including an optical lens array, the optical lens array including at least one non-uniform lens, the non-uniform lens having at least two curvatures.

[0007] Optionally, the lens surface of the non-uniform lens includes at least two sub-surfaces, the radii of the at least two sub-surfaces are different, and the at least two sub-surfaces correspond one-to-one with the at least two curvatures.

[0008] Optionally, the optical lens array includes a plurality of non-uniform lenses with identical structures.

[0009] Optionally, the fingerprint recognition component further includes a display component and a fingerprint sensing component, with the optical lens array located between the display component and the fingerprint sensing component.

[0010] According to a second aspect of the present disclosure, a terminal is provided, the terminal including a fingerprint recognition component as described in the first aspect.

[0011] According to a third aspect of the present disclosure, a fingerprint recognition method is provided, applied to a terminal, the method comprising:

[0012] Based on the current fingerprint information collected by the fingerprint recognition component, at least two current fingerprint images are determined, wherein the fingerprint recognition component is the fingerprint recognition component as described in the first aspect, the fingerprint recognition component has at least two curvatures, and the at least two current fingerprint images correspond one-to-one with the at least two curvatures;

[0013] The fingerprint recognition result is determined based on the preset fingerprint image and the at least two current fingerprint images.

[0014] Optionally, determining the fingerprint recognition result based on the preset fingerprint image and the at least two current fingerprint images includes:

[0015] If the preset fingerprint image includes at least two first fingerprint images, then each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. Here, at least two first fingerprint images correspond one-to-one with at least two curvatures, and the corresponding first fingerprint images and the current fingerprint image are those corresponding to the same curvature; or...

[0016] If the preset fingerprint image includes at least two first fingerprint images, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image, and the at least two first fingerprint images are coupled according to the preset coupling information to determine a second fingerprint image. Then, the third fingerprint image is compared with the second fingerprint image to determine the fingerprint recognition result, wherein at least two first fingerprint images correspond one-to-one with at least two types of curvature; or...

[0017] If the preset fingerprint image includes a second fingerprint image, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image. The third fingerprint image is then compared with the second fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two types of curvature. Alternatively...

[0018] If the preset fingerprint image includes a second fingerprint image, then the second fingerprint image is decoupled according to the preset decoupling information to determine at least two first fingerprint images. Each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two curvatures.

[0019] Optionally, comparing each set of corresponding first fingerprint images with the current fingerprint image to determine the fingerprint recognition result includes:

[0020] If it is determined that each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful; and / or,

[0021] If it is determined that any set of corresponding first fingerprint images and the current fingerprint image do not match, then the fingerprint recognition result is determined to be a recognition failure.

[0022] According to a fourth aspect of the present disclosure, a fingerprint recognition device is provided for use in a terminal, the device comprising:

[0023] The determining module is used to determine at least two current fingerprint images based on the current fingerprint information collected by the fingerprint recognition component, wherein the fingerprint recognition component is the fingerprint recognition component as described in the first aspect, the fingerprint recognition component has at least two curvatures, and the at least two current fingerprint images correspond one-to-one with the at least two curvatures;

[0024] It is also used to determine the fingerprint recognition result based on the preset fingerprint image and the at least two current fingerprint images.

[0025] Optionally, the determining module is configured to:

[0026] If the preset fingerprint image includes at least two first fingerprint images, then each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. Here, at least two first fingerprint images correspond one-to-one with at least two curvatures, and the corresponding first fingerprint images and the current fingerprint image are those corresponding to the same curvature; or...

[0027] If the preset fingerprint image includes at least two first fingerprint images, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image, and the at least two first fingerprint images are coupled according to the preset coupling information to determine a second fingerprint image. Then, the third fingerprint image is compared with the second fingerprint image to determine the fingerprint recognition result, wherein at least two first fingerprint images correspond one-to-one with at least two types of curvature; or...

[0028] If the preset fingerprint image includes a second fingerprint image, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image. The third fingerprint image is then compared with the second fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two types of curvature. Alternatively...

[0029] If the preset fingerprint image includes a second fingerprint image, then the second fingerprint image is decoupled according to the preset decoupling information to determine at least two first fingerprint images. Each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two curvatures.

[0030] Optionally, the determining module is configured to:

[0031] If it is determined that each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful; and / or,

[0032] If it is determined that any set of corresponding first fingerprint images and the current fingerprint image do not match, then the fingerprint recognition result is determined to be a recognition failure.

[0033] According to a fifth aspect of the present disclosure, a terminal is provided, the terminal comprising:

[0034] processor;

[0035] Memory used to store the processor's executable instructions;

[0036] The processor is configured to perform the method as described in the third aspect.

[0037] According to a sixth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, which, when instructions in the storage medium are executed by a processor of a terminal, enables the terminal to perform the method described in the third aspect.

[0038] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: the fingerprint image of a 3D real fingerprint (e.g., a finger fingerprint) collected by the fingerprint recognition component is different from the fingerprint image of a 2D fake fingerprint (e.g., a fingerprint photograph) collected, thereby better achieving anti-counterfeiting of 2D fake fingerprints and improving security.

[0039] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0040] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0041] Figure 1 This is a schematic diagram (including a finger) of a fingerprint recognition component according to an exemplary embodiment.

[0042] Figure 1a This is a schematic diagram of a fingerprint recognition component related to the technology.

[0043] Figure 1b This is a schematic diagram illustrating the recognition principle of fingerprint recognition components in related technologies.

[0044] Figure 1c This is a schematic diagram illustrating the recognition principle of a fingerprint recognition component according to an exemplary embodiment.

[0045] Figure 1d This is a schematic diagram illustrating the recognition principle of a fingerprint recognition component according to an exemplary embodiment.

[0046] Figure 2 This is a flowchart illustrating a fingerprint recognition method according to an exemplary embodiment.

[0047] Figure 3 This is a block diagram illustrating a fingerprint recognition device according to an exemplary embodiment.

[0048] Figure 4 This is a block diagram of a terminal according to an exemplary embodiment. Detailed Implementation

[0049] 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 numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0050] This disclosure provides a fingerprint recognition component. The fingerprint recognition component acquires a 3D fingerprint image of a genuine fingerprint (e.g., a finger's fingerprint), which differs from the acquired 2D fake fingerprint image (e.g., a fingerprint photograph), thereby better preventing 2D fake fingerprints and improving security.

[0051] In one exemplary embodiment, a fingerprint recognition component is provided, which may include an optical lens array 1, the optical lens array 1 including at least one non-uniform lens 11, the non-uniform lens 11 including at least two curvatures.

[0052] When the fingerprint recognition component collects fingerprint information, the light reflected from the fingerprint passes through the non-uniform lens 11, forming two focal points with different focal lengths, meaning the distances between the two focal points and the non-uniform lens 11 are different. Therefore, the fingerprint information of a 3D genuine fingerprint (e.g., a finger's fingerprint) collected by the fingerprint recognition component (which can be recorded as preset fingerprint information) differs from the fingerprint information of a 2D fake fingerprint (e.g., a fingerprint photograph) collected (which can be recorded as current fingerprint information). In other words, the feature points in the preset fingerprint information and the current fingerprint information cannot be correctly matched. This allows for the prevention of 2D fake fingerprints and improves security.

[0053] Understandably, the more non-uniform lenses 11 included in the optical lens array 1, the higher the reliability of its 2D fake fingerprint anti-counterfeiting.

[0054] The optical lens array 1 may include multiple non-uniform lenses 11. For example, in this fingerprint recognition component, the optical lens array 1 is composed of multiple non-uniform lenses 11, that is, all lenses in the optical lens array 1 are non-uniform lenses 11, so as to improve the reliability of anti-counterfeiting of 2D fake fingerprints.

[0055] Among them, multiple non-uniform lenses 11 can have the same structure, so as to facilitate the fabrication and arrangement of the optical lens array 1, simplify the structure of the fingerprint recognition component, reduce the complexity of the fingerprint recognition method, reduce the amount of data processing during fingerprint recognition, etc.

[0056] In this case, the lens surface of a non-uniform lens may include at least two sub-surfaces, the radii of which are different, and each sub-surface corresponds one-to-one with at least two curvatures. That is, the radius of each sub-surface corresponds to a curvature.

[0057] For example, refer to Figure 1c As shown, the non-uniform lens includes two curvatures. In this case, the lens surface of the non-uniform lens includes two sub-surfaces with different radii. The sub-surface 111 with the smaller radius is more convex than the sub-surface 112 with the larger radius, resulting in the non-uniform lens including a convex region and a concave region. The convex region refers to the area corresponding to sub-surface 111, and the concave region refers to the area corresponding to sub-surface 112. The convex and concave regions have different curvatures, thus realizing that the non-uniform lens includes two curvatures.

[0058] It should be noted that this non-uniform lens does not impose restrictions on the differences in curvature; theoretically, any difference in curvature is acceptable. However, in practical use, the thickness of the region corresponding to the minimum curvature in the non-uniform lens will be determined based on the space reserved in the fingerprint recognition module to ensure proper installation of the non-uniform lens.

[0059] Additionally, the fingerprint recognition component may also include a display assembly 2 and a fingerprint sensing component 3. The display assembly 2 may include a display screen and a glass cover, and the fingerprint sensing component 3 may be composed of a fingerprint recognition sensor. The user can place their finger on the display assembly 2, and then the fingerprint information is collected through the optical lens array 1 and the fingerprint sensing component 3.

[0060] The fingerprint recognition component may also include a reinforcing component 4 (e.g., a reinforcing steel sheet). The reinforcing component 4 is located on the side of the fingerprint sensing component 3 away from the optical lens array 1. That is, the fingerprint sensing component 3 is located between the optical lens array 1 and the reinforcing component 4. The reinforcing component 4 is used to support the fingerprint sensing component 3, the optical lens array 1 and the display component 2 to improve the structural stability of the entire fingerprint recognition component.

[0061] It should be noted that the reference Figure 1a and Figure 1b As shown, in the fingerprint recognition component of the related technology, the optical lens array 1' is composed of multiple symmetrical and uniform lenses 11', and the light reflected from the fingerprint has only one focal point, which is denoted as focal point P0. In this fingerprint recognition component, whether it is a 3D true fingerprint or a fake 2D fingerprint, the image after passing through the optical lens array 1' is converged on the fingerprint recognition sensor where the focal point is located.

[0062] refer to Figure 1 and Figure 1c As shown, in the fingerprint recognition component of this disclosure, the optical lens array 1 can be composed of multiple non-uniform lenses 11. The characteristic of the non-uniform lens 11 is that the curvature of the lens is not unique; multiple different curvatures can be designed for the non-uniform lens 11. Specifically, some areas of the non-uniform lens 11 are concave, and some areas are convex, and multiple concave and convex areas can be configured.

[0063] The following description uses a non-uniform lens 11 with two different curvatures as an example. In this non-uniform lens 11, two focal points with different focal lengths will be generated.

[0064] The light reflected from the 3D fingerprint 30 of a real finger passes through the non-uniform lens 11, resulting in two focal lengths for the fingerprint image. Each focal length corresponds one-to-one with the curvature of the non-uniform lens 11; that is, multiple focal lengths are generated when the non-uniform lens 11 has multiple curvatures. The fingerprint recognition sensor component acquires fingerprint images at both focal lengths, with each fingerprint image corresponding to one of the two curvatures. Then, the two fingerprint images are coupled using a coupling algorithm to obtain the final preset fingerprint image.

[0065] The coupling algorithm can be determined based on the fingerprint recognition component. For example, once the structure of the fingerprint recognition component is determined, the coupling algorithm of the fingerprint recognition component can be determined through experiments, and then the determined coupling algorithm can be stored in the terminal.

[0066] Since the focal length is determined by the non-uniform lens 11, and the 3D true fingerprint 30 has valleys and ridges of varying heights, with different distances between the valleys and ridges and the non-uniform lens 11, the valleys, being farther from the non-uniform lens 11, produce images with thicker lines, while the ridges, being closer to the non-uniform lens 11, produce images with thinner lines. In contrast, the lines in the images generated by the valleys and ridges in a fake 2D fingerprint differ in thickness from those in the images generated by the 3D true fingerprint.

[0067] The process by which a 3D true fingerprint 30 generates an image after passing through an optical lens array 1 composed of non-uniform lenses 11 is called image coupling. Since the structure of the fingerprint recognition component is determined, the focal length corresponding to the non-uniform lenses 11 in the optical lens array 1 is known information, so the coupling algorithm and decoupling algorithm can be determined.

[0068] Among them, the coupling algorithm and the decoupling algorithm are inverse algorithms of each other, and the coupling processing based on the coupling algorithm and the decoupling processing based on the decoupling algorithm are inverse processing of each other.

[0069] refer to Figure 1d As shown, since the 2D fake fingerprint 20 is planar, there is no height (depth) between the valleys and ridges. Therefore, when the fingerprint recognition component of this disclosure recognizes the 2D fake fingerprint 20, the two focal points generated by the valleys and ridges are as follows: Figure 4 As shown in the diagram, focal point P3 and focal point P4 are given. The focal length corresponding to focal point P3 can be denoted as d3, and the focal length corresponding to focal point P4 can be denoted as d4.

[0070] When the fingerprint recognition component of this disclosure recognizes a 3D true fingerprint 30, the two focal points generated by the valleys and ridges are as follows: Figure 4 The focal points P1 and P2 are shown in the figure, where the focal length corresponding to focal point P1 is denoted as focal length d1, and the focal length corresponding to focal point P2 is denoted as focal length d2.

[0071] In this case, d1, d2, d3, and d4 are all different, therefore, the image size at this focal length is also different. That is, the valley images of a 3D genuine fingerprint differ in thickness from those of a 2D fake fingerprint, and the ridge images of a 3D genuine fingerprint differ in thickness from those of a 2D fake fingerprint. Thus, the fingerprint image of the 2D fake fingerprint 20 acquired by the fingerprint recognition component is different from the fingerprint image of the 3D genuine fingerprint 30 acquired by it. Therefore, anti-counterfeiting identification of the 2D fake fingerprint 20 can be achieved, improving security.

[0072] When this fingerprint recognition component is applied to a terminal, it is understood that the images of focus P1 and focus P2 generated by the 3D true fingerprint 30 are those of the real finger used by the user during the initial fingerprint registration. The image points generated after the real finger is registered are recorded as focus P1 and focus P2. If the user uses the 2D fake fingerprint 20 to unlock the terminal, the terminal will determine that it does not match the previously registered fingerprint information, and the unlocking will fail.

[0073] However, it's important to note that if a 2D fake fingerprint (20) was used during initial registration, the 2D fake fingerprint will not be able to be used for anti-counterfeiting identification when the user tries to unlock the device. Furthermore, the user will also be unable to unlock the device using the 3D real fingerprint (30); that is, when the user tries to unlock the device using the 3D real fingerprint (30), it will be considered as not matching the previously registered fingerprint information.

[0074] The fingerprint recognition component has a simple structure and low cost. Furthermore, the design of the optical lens array 1 is flexible and easy to change. With the combination of coupling and decoupling algorithms, different levels of encryption and anti-counterfeiting can be achieved, thereby improving the security of optical fingerprint recognition.

[0075] In this fingerprint recognition component, due to the presence of a non-uniform lens 11, the fingerprint information of the 3D true fingerprint of the real finger it collects is different from the fingerprint information of the 2D fake fingerprint (such as a fingerprint photo) it collects. This can better achieve anti-counterfeiting of 2D fake fingerprints and improve security.

[0076] In one exemplary embodiment, a terminal is provided, such as a mobile phone, laptop computer, tablet computer, and wearable device. This terminal can utilize the aforementioned fingerprint recognition component to prevent 2D fake fingerprints, thereby improving terminal security and enhancing the user experience.

[0077] In one exemplary embodiment, a fingerprint recognition method is provided, applied to the aforementioned terminal. (Reference) Figure 2 As shown, the method includes:

[0078] S110. Based on the current fingerprint information collected by the fingerprint recognition component, determine at least two current fingerprint images;

[0079] S120. Determine the fingerprint recognition result based on the pre-printed image and at least two current fingerprint images.

[0080] In step S110, the current fingerprint information refers to the information of the fingerprint currently placed on the fingerprint recognition component, collected by the fingerprint recognition component. For example, the fingerprint information currently used to unlock the terminal, collected by the fingerprint recognition component.

[0081] The fingerprint recognition component can be the fingerprint recognition component described in the other embodiments above. The fingerprint recognition component may have at least two curvatures, each curvature corresponding to a focal length, that is, the fingerprint recognition component has at least two focal lengths, wherein at least two current fingerprint images, at least two curvatures, and at least two focal lengths correspond one-to-one.

[0082] Example 1,

[0083] The fingerprint recognition component has two curvatures, denoted as the first curvature and the second curvature. After acquiring the current fingerprint information, the fingerprint recognition component can determine the current fingerprint image D1 based on the fingerprint information corresponding to the first curvature, and determine the current fingerprint image D2 based on the fingerprint information corresponding to the second curvature. In other words, two current fingerprint images are determined based on the current fingerprint information, namely the aforementioned current fingerprint image D1 and current fingerprint image D2, where current fingerprint image D1 corresponds to the first curvature and current fingerprint image D2 corresponds to the second curvature.

[0084] In step S120, the preset fingerprint image may include at least two first fingerprint images.

[0085] The number of first fingerprint images is the same as the type of curvature. That is, when the fingerprint recognition component has at least two curvatures, the number of first fingerprint images is at least two, and at least two first fingerprint images correspond one-to-one with at least two curvatures. The method for determining the first fingerprint image is similar to the method for acquiring the current fingerprint image; it can be determined by the preset fingerprint information acquired by the fingerprint recognition module.

[0086] The first fingerprint image can be directly preset on the terminal. For example, the user can place the finger they want to use for unlocking on the display screen of the fingerprint recognition component. The optical lens array and fingerprint sensing component of the fingerprint recognition component can then collect the fingerprint information of the finger and determine the fingerprint information corresponding to each curvature as the first fingerprint image corresponding to that curvature.

[0087] The fingerprint recognition result is determined based on a preset fingerprint image and at least two current fingerprint images, which can include two methods.

[0088] Method 1,

[0089] S121. Compare each pair of corresponding first fingerprint images with the current fingerprint image to determine the fingerprint recognition result.

[0090] Among them, the first fingerprint image and the current fingerprint image that correspond to each other are the first fingerprint image and the current fingerprint image that correspond to the same curvature.

[0091] It should be noted that, generally speaking, the fingerprint ridges are not continuous, smooth, and straight, but often have interruptions, forks, or turns. These breakpoints, forks, and turns are called feature points. In this step, comparisons can be made based on these feature points.

[0092] During the comparison, the first fingerprint image corresponding to the same curvature and the current fingerprint image need to be compared in terms of feature points. Then, it is determined whether the first fingerprint image corresponding to that curvature and the current fingerprint image match. Finally, based on the comparison results of the first fingerprint images corresponding to all curvatures and the current fingerprint images, the final fingerprint recognition result is determined.

[0093] If each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful.

[0094] Example 2,

[0095] The fingerprint recognition component has two curvatures, denoted as the first curvature and the second curvature. The terminal has two preset first fingerprint images, denoted as first fingerprint image P1 and first fingerprint image P2. First fingerprint image P1 is the fingerprint image formed under the first curvature; that is, first fingerprint image P1 corresponds to the first curvature. First fingerprint image P2 is the fingerprint image formed under the second curvature; that is, first fingerprint image P2 corresponds to the second curvature.

[0096] In this example, after the fingerprint recognition component acquires the current fingerprint information, it can determine the current fingerprint image D1 based on the fingerprint information corresponding to the first curvature, and determine the current fingerprint image D2 based on the fingerprint information corresponding to the second curvature. Specifically, the current fingerprint image D1 corresponds to the first curvature, and the current fingerprint image D2 corresponds to the second curvature.

[0097] In this example, during fingerprint recognition, the current fingerprint image D1 is compared with the first fingerprint image P2 by feature point comparison to determine if they match. Similarly, the current fingerprint image D2 is compared with the first fingerprint image P2 by feature point comparison to determine if they match.

[0098] In this example, if it is determined that the current fingerprint image D1 matches the first fingerprint image, and the current fingerprint image D2 matches the first fingerprint image P2, then the fingerprint recognition result can be determined as successful.

[0099] If any pair of corresponding first fingerprint images and the current fingerprint image are determined to be mismatched, the fingerprint recognition result is determined to be a recognition failure.

[0100] Example 3,

[0101] The fingerprint recognition component has two curvatures, denoted as the first curvature and the second curvature. The terminal has two preset first fingerprint images, denoted as first fingerprint image P1 and first fingerprint image P2. First fingerprint image P1 corresponds to the first curvature, and first fingerprint image P2 corresponds to the second curvature.

[0102] In this example, after the fingerprint recognition component acquires the current fingerprint information, it can determine the current fingerprint image D1 based on the fingerprint information corresponding to the first curvature, and determine the current fingerprint image D2 based on the fingerprint information corresponding to the second curvature. Specifically, the current fingerprint image D1 corresponds to the first curvature, and the current fingerprint image D2 corresponds to the second curvature.

[0103] In this example, when performing fingerprint recognition, it is necessary to compare the feature points of the current fingerprint image D1 with the first fingerprint image P2, and then compare the feature points of the current fingerprint image D2 with the first fingerprint image P2.

[0104] In this example, a fingerprint recognition result can be determined to be a failure if any of the following three conditions are met:

[0105] Case 1: It is determined that the current fingerprint image D1 does not match the first fingerprint image P1;

[0106] Case 2: It is determined that the current fingerprint image D2 does not match the first fingerprint image P2;

[0107] Case 1: It is determined that the current fingerprint image D1 does not match the first fingerprint image P1, and it is also determined that the current fingerprint image D2 does not match the first fingerprint image P2.

[0108] It should be noted that if the current fingerprint image is a 2D fake fingerprint image, while the first fingerprint image is a 3D real fingerprint image, then although the current fingerprint image and the first fingerprint image correspond to the same curvature, their focal lengths are different. Therefore, the thickness of the images corresponding to the same fingerprint is different, and the two fingerprint images will inevitably be different. When comparing feature points, it will be determined that the two do not match.

[0109] In addition, when the fingerprint recognition module includes three or more curvatures, the fingerprint recognition result can also be determined by other methods, which are not limited here.

[0110] For example, a percentage threshold can be set to compare the first fingerprint image and the current fingerprint image in each corresponding group. If the percentage of matching groups is greater than or equal to the percentage threshold, the fingerprint recognition result is considered successful; otherwise, the fingerprint recognition result is considered unsuccessful. Alternatively, the fingerprint recognition result can be determined in other ways. For instance, a group number threshold can be set. Only when the number of matching groups is greater than or equal to the group number threshold will the fingerprint recognition result be considered successful.

[0111] Method 2,

[0112] S12-1. Perform coupling processing on all first fingerprint images according to preset coupling information to determine the second fingerprint image.

[0113] S12-2. Perform coupling processing on all current fingerprint images according to preset coupling information to determine the third fingerprint image.

[0114] S12-3. Compare the third fingerprint image with the second fingerprint image to determine the fingerprint recognition result.

[0115] In step S12-1, the preset coupling information is determined based on the fingerprint recognition component. The preset coupling information can be a coupling algorithm. For example, once the structure of the fingerprint recognition component is determined, experiments can be conducted on the fingerprint recognition component to determine its coupling information, and then the determined coupling information is stored in the terminal as preset coupling information.

[0116] The preset coupling information can be set before or after the terminal leaves the factory, which will not be elaborated here.

[0117] In this step, once all the first fingerprint images have been determined, all the set fingerprint patterns can be coupled according to the preset coupling information to process all the first fingerprint images into a second fingerprint image.

[0118] It's important to note that coupling occurs because the optical lens array in the fingerprint recognition component has more than one curvature. Different curvatures produce first fingerprint images with different focal lengths. The image coupling process involves superimposing these first fingerprint images with different focal lengths. After multiple first fingerprint images are superimposed, a second fingerprint image is formed. The fingerprint patterns in the second fingerprint image are formed by superimposing the fingerprint patterns from all the first fingerprint images. Therefore, the coupled second fingerprint image has new fingerprint patterns that are correlated with the focal length (curvature).

[0119] In step S12-2, the method of coupling at least two current fingerprint images to obtain a third fingerprint image is the same as the method of coupling at least two first fingerprint images to obtain a second fingerprint image, and will not be described in detail here.

[0120] In step S12-3, during the comparison, the feature points of the third fingerprint image and the second fingerprint image need to be compared to determine whether they match. Then, based on the comparison results, the final fingerprint recognition result is determined.

[0121] If the third fingerprint image matches the second fingerprint image, the fingerprint recognition result is considered successful. If the third fingerprint image does not match the second fingerprint image, the fingerprint recognition result is considered unsuccessful.

[0122] It should be noted that if the current fingerprint image is a 2D fake fingerprint image, then although the current fingerprint image and the first fingerprint image correspond to the same curvature, their focal lengths are different. Therefore, the thickness of the corresponding images is different, and the two fingerprint images will inevitably be different. Thus, the third fingerprint image obtained by coupling based on the current fingerprint image will necessarily be different from the second fingerprint image obtained by coupling based on the first fingerprint image. Based on this, fingerprint anti-counterfeiting identification can be achieved.

[0123] In this method, since the optical lens array in the fingerprint recognition component includes non-uniform lenses, the first fingerprint image of the 3D true fingerprint acquired by the fingerprint recognition component is different from the current fingerprint image of the acquired 2D fake fingerprint (e.g., fingerprint photograph), thereby better realizing the anti-counterfeiting of 2D fake fingerprints and improving security.

[0124] In one exemplary embodiment, a fingerprint recognition method is provided, applied to a terminal. In this method, a preset fingerprint image may include a second fingerprint image. The preset fingerprint image can be determined based on fingerprint information from a 3D true fingerprint. The terminal can acquire fingerprint information from a 3D true fingerprint using a fingerprint recognition component, and then obtain the aforementioned second fingerprint image. Alternatively, the terminal can directly download a second fingerprint image determined by another terminal from a network.

[0125] In this method, the second fingerprint image can be determined in the following way:

[0126] S210. Based on the set fingerprint information collected by the fingerprint recognition component, determine at least two first fingerprint images;

[0127] S220. Perform coupling processing on all first fingerprint images according to preset coupling information to determine the second fingerprint image.

[0128] In step S211, the method for obtaining the first fingerprint image is similar to the method for obtaining the current fingerprint image, and will not be described in detail here. For example, a 3D real fingerprint (such as a human finger) is placed at the corresponding position of the fingerprint recognition component, and the fingerprint recognition component can collect the fingerprint information of the 3D real fingerprint, and then obtain at least two first fingerprint images. Among them, each curvature corresponds to one first fingerprint image.

[0129] In step S212, the preset coupling information is determined based on the fingerprint recognition component, and the preset coupling information can be a coupling algorithm. For example, once the structure of the fingerprint recognition component is determined, experiments can be conducted on the fingerprint recognition component to determine its coupling information, and then the determined coupling information is stored in the terminal as preset coupling information.

[0130] The preset coupling information can be set before or after the terminal leaves the factory, which will not be elaborated here.

[0131] In this step, once all the first fingerprint images are determined, they can be coupled according to preset coupling information to convert them into a single second fingerprint image for storage on the terminal. Furthermore, since the terminal stores the second fingerprint image instead of directly storing the first fingerprint image, it is difficult for others to obtain the first fingerprint image without knowing the decoupling information, thus improving security to a certain extent.

[0132] For example, a user can place their finger on the display screen of a fingerprint recognition component. The optical lens array and fingerprint sensing component of the fingerprint recognition component can then acquire the fingerprint information of the finger, obtaining at least two first fingerprint images. Then, coupling information is used to couple all the first fingerprint images to obtain a coupled second fingerprint image.

[0133] It's important to note that coupling occurs because the optical lens array in the fingerprint recognition component has more than one curvature. Different curvatures produce first fingerprint images with different focal lengths. The image coupling process involves superimposing these first fingerprint images with different focal lengths. After multiple first fingerprint images are superimposed, a second fingerprint image is formed. The fingerprint patterns in the second fingerprint image are formed by superimposing the fingerprint patterns from all the first fingerprint images. Therefore, the coupled second fingerprint image has new fingerprint patterns that are correlated with the focal length (curvature).

[0134] In this method, the fingerprint recognition result is determined based on a preset fingerprint image and at least two current fingerprint images, which may include two methods.

[0135] Method 1,

[0136] S310. Decouple the second fingerprint image according to the preset decoupling information to determine at least two first fingerprint images;

[0137] S320. Compare each pair of corresponding first fingerprint images with the current fingerprint image to determine the fingerprint recognition result.

[0138] In step S310, the preset decoupling information can be a decoupling algorithm, and the coupling algorithm and the decoupling algorithm are inverse algorithms of each other.

[0139] The method for determining preset decoupling information is similar to that for preset coupling information. Preset decoupling information is also determined based on the fingerprint recognition component. For example, once the structure of the fingerprint recognition component is determined, experiments can be conducted on the fingerprint recognition component to determine its decoupling information. Then, the determined decoupling information is stored in the terminal as preset decoupling information.

[0140] The preset decoupling information can be set before or after the terminal leaves the factory, which will not be elaborated here.

[0141] In this step, the preset second fingerprint image can be decoupled based on the preset decoupling information of the terminal to obtain at least two first fingerprint images (i.e., all first fingerprint images). Among them, the above-mentioned at least two first fingerprint images correspond one-to-one with at least two curvatures.

[0142] It's important to note that decoupling is essentially the reverse of coupling. However, this process requires prior knowledge of the curvature of the fingerprint recognition component and the corresponding focal length for each curvature. These parameters are necessary to decouple the coupled second fingerprint image, resulting in at least two first fingerprint images. The decoupling process involves filtering the ridges in the second fingerprint image at different focal lengths. The fingerprint ridge threshold obtained through the decoupling focal length filter determines the first fingerprint image that matches the corresponding focal length.

[0143] Step S320 is the same as step S121 in other embodiments, and will not be described again here.

[0144] Method 2,

[0145] S410. Perform coupling processing on at least two current fingerprint images according to preset coupling information to determine a third fingerprint image;

[0146] S420. Compare the third fingerprint image with the second fingerprint image to determine the fingerprint recognition result.

[0147] In step S410, the method of coupling at least two current fingerprint images to obtain a third fingerprint image is the same as the method of coupling at least two first fingerprint images to obtain a second fingerprint image, and will not be described in detail here.

[0148] In step S420, during the comparison, the feature points of the third fingerprint image and the second fingerprint image need to be compared to determine whether they match. Then, based on the comparison result, the final fingerprint recognition result is determined.

[0149] If the third fingerprint image matches the second fingerprint image, the fingerprint recognition result is considered successful. If the third fingerprint image does not match the second fingerprint image, the fingerprint recognition result is considered unsuccessful.

[0150] It should be noted that if the current fingerprint image is a 2D fake fingerprint image, then although the current fingerprint image and the first fingerprint image correspond to the same curvature, their focal lengths are different. Therefore, the thickness of the corresponding images is different, and the two fingerprint images will inevitably be different. Thus, the third fingerprint image obtained by coupling based on the current fingerprint image will necessarily be different from the second fingerprint image obtained by coupling based on the first fingerprint image. Based on this, fingerprint anti-counterfeiting identification can be achieved.

[0151] In addition, the decoupling process causes some image loss, and some images may be miscoupled or cannot be decoupled. Therefore, fingerprint recognition based on the coupled second fingerprint image and the coupled third fingerprint image can improve the recognition accuracy.

[0152] In this method, since the optical lens array in the fingerprint recognition component includes non-uniform lenses, the first fingerprint image of the 3D true fingerprint acquired by the fingerprint recognition component is different from the current fingerprint image of the acquired 2D fake fingerprint (e.g., fingerprint photograph), thereby better realizing the anti-counterfeiting of 2D fake fingerprints and improving security.

[0153] In one exemplary embodiment, a fingerprint recognition device is provided, applied to the aforementioned terminal. This device is used to implement the fingerprint recognition method described above. (Reference) Figure 3 As shown, the device may include a determining module 101, wherein,

[0154] The determining module 101 is used to determine at least two current fingerprint images based on the current fingerprint information collected by the fingerprint recognition component, wherein the fingerprint recognition component is the aforementioned fingerprint recognition component, the fingerprint recognition component has at least two curvatures, and the at least two current fingerprint images correspond one-to-one with the at least two curvatures;

[0155] It is also used to determine the fingerprint recognition result based on a preset fingerprint image and at least two current fingerprint images.

[0156] In one exemplary embodiment, a fingerprint recognition device is provided, applied to the aforementioned terminal. (Reference) Figure 3 As shown, in this device, the determining module 101 is used for:

[0157] If the preset fingerprint image includes at least two first fingerprint images, then each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. Here, at least two first fingerprint images correspond one-to-one with at least two curvatures, and the corresponding first fingerprint images and the current fingerprint image are those corresponding to the same curvature; or...

[0158] If the preset fingerprint image includes at least two first fingerprint images, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image, and the at least two first fingerprint images are coupled according to preset coupling information to determine a second fingerprint image. Then, the third fingerprint image is compared with the second fingerprint image to determine the fingerprint recognition result, wherein at least two first fingerprint images correspond one-to-one with at least two curvatures; or,

[0159] If the preset fingerprint image includes a second fingerprint image, then at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image. The third fingerprint image is then compared with the second fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two curvatures; or...

[0160] If the preset fingerprint image includes a second fingerprint image, then the second fingerprint image is decoupled according to the preset decoupling information to determine at least two first fingerprint images. Each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information. The at least two first fingerprint images correspond one-to-one with at least two curvatures.

[0161] In one exemplary embodiment, a fingerprint recognition device is provided, applied to the aforementioned terminal. (Reference) Figure 3 As shown, in this device, the determining module 101 is used for:

[0162] If it is determined that each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful; and / or,

[0163] If it is determined that any set of corresponding first fingerprint images and the current fingerprint image do not match, then the fingerprint recognition result is determined to be a recognition failure.

[0164] In one exemplary embodiment, a terminal is provided, such as a mobile phone, laptop computer, tablet computer, and wearable device. The terminal may include the fingerprint recognition component described in the above embodiments.

[0165] refer to Figure 4 The terminal 400 may include one or more of the following components: a processing component 402, a memory 404, a power supply component 406, a multimedia component 408, an audio component 410, an input / output (I / O) interface 412, a sensor component 414, and a communication component 416.

[0166] Processing component 402 typically controls the overall operation of terminal 400, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 402 may include one or more processors 420 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 402 may include one or more modules to facilitate interaction between processing component 402 and other components. For example, processing component 402 may include a multimedia module to facilitate interaction between multimedia component 408 and processing component 402.

[0167] Memory 404 is configured to store various types of data to support operation on terminal 400. Examples of this data include instructions for any application or method operating on terminal 400, contact data, phonebook data, messages, pictures, videos, etc. Memory 404 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0168] Power supply component 406 provides power to various components of terminal 400. Power supply component 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to terminal 400.

[0169] Multimedia component 408 includes a screen that provides an output interface between terminal 400 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 408 includes a front-facing camera module and / or a rear-facing camera module. When terminal 400 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera module and / or the rear-facing camera module may receive external multimedia data. Each front-facing camera module and rear-facing camera module may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0170] Audio component 410 is configured to output and / or input audio signals. For example, audio component 410 includes a microphone (MIC) configured to receive external audio signals when terminal 400 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 404 or transmitted via communication component 416. In some embodiments, audio component 410 also includes a speaker for outputting audio signals.

[0171] I / O interface 412 provides an interface between processing component 402 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0172] Sensor assembly 414 includes one or more sensors for providing state assessments of various aspects of terminal 400. For example, sensor assembly 414 may detect the on / off state of terminal 400, the relative positioning of components such as the display and keypad of terminal 400, changes in the position of terminal 400 or a component of terminal 400, the presence or absence of user contact with terminal 400, the orientation or acceleration / deceleration of terminal 400, and temperature changes of terminal 400. Sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 414 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 414 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0173] Communication component 416 is configured to facilitate wired or wireless communication between terminal 400 and other terminals. Terminal 700 can access wireless networks based on communication standards, such as WiFi, 2G, 3G, 4G, 5G, or combinations thereof. In one exemplary embodiment, communication component 416 receives broadcast signals or broadcast-related signals from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 416 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0174] In an exemplary embodiment, terminal 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing terminals (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0175] In one exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 404 including instructions, which can be executed by a processor 420 of a terminal 400 to perform the described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage terminal, etc. When the instructions in the storage medium are executed by the terminal's processor, the terminal is able to perform the method shown in the above embodiments.

[0176] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0177] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0178] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A fingerprint recognition component, characterized in that, The fingerprint recognition component includes an optical lens array, which includes at least one non-uniform lens having at least two curvatures. The fingerprint recognition component is used to acquire current fingerprint information, and at least two current fingerprint images determined based on the current fingerprint information correspond one-to-one with the at least two curvatures.

2. The fingerprint recognition component according to claim 1, characterized in that, The lens surface of the non-uniform lens includes at least two sub-surfaces, the radii of the at least two sub-surfaces are different, and the at least two sub-surfaces correspond one-to-one with the at least two curvatures.

3. The fingerprint recognition component according to claim 1, characterized in that, The optical lens array includes multiple non-uniform lenses with identical structures.

4. The fingerprint recognition component according to any one of claims 1-3, characterized in that, The fingerprint recognition component further includes a display component and a fingerprint sensing component, with the optical lens array located between the display component and the fingerprint sensing component.

5. A terminal, characterized in that, The terminal includes a fingerprint recognition component as described in any one of claims 1-4.

6. A fingerprint recognition method, applied to a terminal, characterized in that, The method includes: Based on the current fingerprint information collected by the fingerprint recognition component, at least two current fingerprint images are determined, wherein the fingerprint recognition component is the fingerprint recognition component as described in any one of claims 1-4, the fingerprint recognition component has at least two curvatures, and the at least two current fingerprint images correspond one-to-one with the at least two curvatures; The fingerprint recognition result is determined based on the preset fingerprint image and the at least two current fingerprint images.

7. The method according to claim 6, characterized in that, The step of determining the fingerprint recognition result based on the preset fingerprint image and the at least two current fingerprint images includes: If the preset fingerprint image includes at least two first fingerprint images, then each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. Here, at least two first fingerprint images correspond one-to-one with at least two curvatures, and the corresponding first fingerprint images and the current fingerprint image are those corresponding to the same curvature; or... If the preset fingerprint image includes at least two first fingerprint images, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image, and the at least two first fingerprint images are coupled according to the preset coupling information to determine a second fingerprint image. Then, the third fingerprint image is compared with the second fingerprint image to determine the fingerprint recognition result, wherein at least two first fingerprint images correspond one-to-one with at least two types of curvature; or... If the preset fingerprint image includes a second fingerprint image, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image. The third fingerprint image is then compared with the second fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two types of curvature. Alternatively... If the preset fingerprint image includes a second fingerprint image, then the second fingerprint image is decoupled according to the preset decoupling information to determine at least two first fingerprint images. Each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two curvatures.

8. The method according to claim 7, characterized in that, The step of comparing each set of corresponding first fingerprint images with the current fingerprint image to determine the fingerprint recognition result includes: If it is determined that each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful; and / or, If it is determined that any set of corresponding first fingerprint images and the current fingerprint image do not match, then the fingerprint recognition result is determined to be a recognition failure.

9. A fingerprint recognition device, applied to a terminal, characterized in that, The device includes: The determining module is used to determine at least two current fingerprint images based on the current fingerprint information collected by the fingerprint recognition component, wherein the fingerprint recognition component is the fingerprint recognition component as described in any one of claims 1-4, the fingerprint recognition component has at least two curvatures, and the at least two current fingerprint images correspond one-to-one with the at least two curvatures; It is also used to determine the fingerprint recognition result based on the preset fingerprint image and the at least two current fingerprint images.

10. The apparatus according to claim 9, characterized in that, The determining module is used for: If the preset fingerprint image includes at least two first fingerprint images, then each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. Here, at least two first fingerprint images correspond one-to-one with at least two curvatures, and the corresponding first fingerprint images and the current fingerprint image are those corresponding to the same curvature; or... If the preset fingerprint image includes at least two first fingerprint images, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image, and the at least two first fingerprint images are coupled according to the preset coupling information to determine a second fingerprint image. Then, the third fingerprint image is compared with the second fingerprint image to determine the fingerprint recognition result, wherein at least two first fingerprint images correspond one-to-one with at least two types of curvature; or... If the preset fingerprint image includes a second fingerprint image, then the at least two current fingerprint images are coupled according to preset coupling information to determine a third fingerprint image. The third fingerprint image is then compared with the second fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two types of curvature. Alternatively... If the preset fingerprint image includes a second fingerprint image, then the second fingerprint image is decoupled according to the preset decoupling information to determine at least two first fingerprint images. Each pair of corresponding first fingerprint images is compared with the current fingerprint image to determine the fingerprint recognition result. The second fingerprint image is obtained by coupling at least two first fingerprint images according to the preset coupling information, and the at least two first fingerprint images correspond one-to-one with at least two curvatures.

11. The apparatus according to claim 10, characterized in that, The determining module is used for: If it is determined that each pair of corresponding first fingerprint images matches the current fingerprint image, then the fingerprint recognition result is determined to be successful; and / or, If it is determined that any set of corresponding first fingerprint images and the current fingerprint image do not match, then the fingerprint recognition result is determined to be a recognition failure.

12. A terminal, characterized in that, The terminal includes: processor; Memory used to store the processor's executable instructions; The processor is configured to perform the method as described in any one of claims 6-8.

13. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the terminal, the terminal is able to perform the method as described in any one of claims 6-8.

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