Curved fingerprint recognition sensor and fingerprint image preprocessing method

Abstract

The present invention provides a fingerprint image preprocessing method, which is applied to a curved surface fingerprint recognition sensor, wherein the curved surface fingerprint recognition sensor includes a curved surface sensing area for placing a finger, and the fingerprint image preprocessing method includes: obtaining a currently sensed curved surface fingerprint image signal; and performing planarization processing on the currently sensed curved surface fingerprint image signal to obtain a preprocessed fingerprint image signal. The above fingerprint image preprocessing method can perform planarization processing on the curved surface fingerprint image signal sensed by the curved surface fingerprint recognition sensor to obtain a preprocessed fingerprint image signal, and perform fingerprint image processing and recognition based on the preprocessed fingerprint image signal. Since the planarized image signal has good plane consistency, it is convenient for post-processing. In addition, the present invention also provides a fingerprint recognition method, a curved surface fingerprint recognition sensor, and an electronic device.

Description

Technical Field

[0001] The present invention relates to the field of fingerprint recognition technology, and in particular to a curved surface fingerprint recognition sensor and a fingerprint image preprocessing method. Background Art

[0002] In order to improve security and user convenience, more and more biometric systems are being used in mobile communication devices, portable tablets and other electronic devices. In particular, capacitive fingerprint chips are increasingly recognized by customers and widely promoted due to their small structure and stable performance.

[0003] With the popularization of full-screen technology and fingerprint recognition technology in mobile terminals, the requirements for fingerprint recognition modules on modern mobile portable devices are getting higher and higher. While the recognition performance and user experience are constantly improving, the size of the fingerprint recognition module in the product is constantly shrinking. Among them, the side fingerprint module set on the power button of the mobile phone has been widely recognized by users and manufacturers. In order to take into account the aesthetics of the product and the user experience, it is a more recognized solution to design the side fingerprint module into an arc shape and combine it with the power button. Specifically, the arc-shaped side fingerprint module generally has the characteristics of being thick in the middle and thin at both ends. When using the fingerprint module for identification, the finger is generally placed in the middle of the fingerprint module. Therefore, the fingerprint is far away from the two ends of the fingerprint module. Therefore, when the fingerprint module uses a capacitive sensor or an optical sensor to collect fingerprint image signals, the fingerprint image signals at both ends will be relatively weak, which will bring difficulties to the subsequent fingerprint matching and identification. Summary of the invention

[0004] In view of this, it is necessary to provide an electronic device that is convenient for processing image signals of a curved fingerprint recognition sensor, a curved fingerprint recognition sensor, a fingerprint image preprocessing method, and a fingerprint recognition method.

[0005] In a first aspect, this embodiment provides a fingerprint image preprocessing method, which is applied to a curved surface fingerprint recognition sensor, wherein the curved surface fingerprint recognition sensor includes a curved surface sensing area for placing a finger, and the fingerprint image preprocessing method includes:

[0006] Acquire the currently sensed curved surface fingerprint image signal; and

[0007] The currently sensed curved surface fingerprint image signal is planarized to obtain a preprocessed fingerprint image signal.

[0008] In a second aspect, the present embodiment further provides a fingerprint recognition method applied to a curved surface fingerprint recognition sensor, wherein the curved surface fingerprint recognition sensor includes a curved surface sensing area for placing a finger, and the fingerprint recognition method includes:

[0009] Acquire a sample fingerprint image signal, wherein the sample fingerprint image signal is a curved surface fingerprint image signal;

[0010] performing planarization processing on the sample fingerprint image signal to obtain a preprocessed sample fingerprint image signal; and

[0011] The preprocessed sample fingerprint image signal is converted into a sample fingerprint image.

[0012] In a third aspect, this embodiment further provides a curved surface fingerprint recognition sensor, the curved surface fingerprint recognition sensor comprising a curved surface sensing area for placing a finger, and the fingerprint recognition method comprising:

[0013] A storage medium for storing fingerprint recognition program instructions; and

[0014] The processor is used to execute the fingerprint recognition program instructions to implement the above-mentioned fingerprint recognition method.

[0015] In a fourth aspect, this embodiment further provides an electronic device, which includes a main body and the above-mentioned curved surface fingerprint recognition sensor arranged on the main body.

[0016] The fingerprint image preprocessing method can planarize the curved fingerprint image signal sensed by the curved fingerprint recognition sensor to obtain a preprocessed fingerprint image signal, and perform fingerprint image processing and recognition based on the preprocessed fingerprint image signal. Since the planarized image signal has good plane consistency, it is convenient for post-processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention 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, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0018] Figure 1 A schematic flow chart of a fingerprint image preprocessing method provided in the first embodiment.

[0019] Figure 2 A schematic diagram of program blocks corresponding to the fingerprint image preprocessing method provided by an embodiment.

[0020] Figure 3 A schematic diagram of the effect of two curve signals with the same distribution in one dimension provided by an embodiment.

[0021] Figure 4 A schematic diagram of the effect of subtracting two curve signals with the same distribution in one dimension provided by an embodiment.

[0022] Figure 5 A schematic diagram of a sub-process of a preprocessing method provided in an embodiment.

[0023] Figure 6 A schematic diagram of a sub-process of the preprocessing method provided in the second embodiment.

[0024] Figure 7 A schematic diagram of the internal structure of a curved surface sensor provided in one embodiment.

[0025] Figure 8 A schematic diagram of an electronic device using a curved surface sensor provided by an embodiment.

[0026] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. The drawings in the specification illustrate examples of embodiments of the present invention. It is understood that the proportions shown in the drawings in the specification are not the proportions of the actual implementation of the present invention. They are only for the purpose of illustrative explanation and are not drawn according to the original size. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate. In other words, the described embodiments are implemented according to a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations may also include other content. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to only those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] It should be noted that the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0030] The present invention provides a fingerprint image preprocessing method, which can be applied to a curved surface fingerprint recognition sensor to planarize the curved surface fingerprint image signal sensed by the curved surface fingerprint recognition sensor to obtain a preprocessed fingerprint image signal, and perform fingerprint image processing and recognition based on the preprocessed fingerprint image signal. Since the planarized image signal has good plane consistency, it is convenient for post-processing.

[0031] Please see Figure 1 and Figure 2 , respectively, are a fingerprint image preprocessing method provided in this embodiment and a schematic diagram of a program block corresponding to the fingerprint image preprocessing method. The fingerprint image preprocessing method is applied to a curved surface fingerprint recognition sensor 1. The fingerprint recognition sensor 1 is provided with a curved surface sensing area 10. The curved surface sensing area 10 can be, but is not limited to, an outwardly convex arc surface or an m-shaped curved surface. Specifically, the fingerprint image preprocessing method includes the following steps.

[0032] Step S101, obtaining the currently sensed curved surface fingerprint image signal S1. It can be understood that the currently sensed curved surface fingerprint image signal S1 is a signal generated by the curved surface fingerprint recognition sensor 1 caused by the finger object currently placed in the curved surface sensing area 10. At this time, the currently sensed curved surface fingerprint recognition image signal S1 is distributed on a curved surface. In this embodiment, the curved surface fingerprint recognition sensor 1 is a capacitive fingerprint recognition sensor. In some feasible embodiments, the curved surface fingerprint recognition sensor 1 can also be an optical fingerprint recognition sensor.

[0033] Step S103, planarizing the currently sensed curved surface fingerprint image signal to obtain a pre-processed fingerprint image signal. Specifically, the curved surface fingerprint image signal S1 that is distributed on a curved surface is roughly distributed on a plane after planarization. In this embodiment, planarizing the currently sensed curved surface fingerprint image signal S1 to obtain the pre-processed fingerprint image signal S2 is specifically: calculating the difference between the currently sensed curved surface fingerprint image signal S1 and the background fingerprint image signal S0 to obtain the pre-processed fingerprint image signal S2. Among them, the background fingerprint image signal S0 is a fingerprint image signal formed by averaging multiple fingerprint image signals S sensed multiple times previously. The background fingerprint image signal S0 is stored in the curved surface fingerprint recognition sensor 1. In this embodiment, the background fingerprint image signal S0 is preset before leaving the factory. Furthermore, the multiple fingerprint image signals sensed multiple times previously are collected for the same finger object, especially when the background fingerprint image signal S0 is set by the user. Collecting for the same finger object can ensure that the produced background fingerprint pattern S0 is more accurate. It can be understood that the finger object corresponding to the currently sensed curved fingerprint image signal S1 is different from the finger object corresponding to the fingerprint image signal S sensed multiple times in advance. In some feasible embodiments, the background fingerprint image signal S0 can also be set by the user. How to make the background fingerprint image signal S0 will be described in detail below.

[0034] Further, in this embodiment, the difference between the currently sensed curved surface fingerprint image signal S1 and the background fingerprint image signal S0 is calculated to obtain the preprocessed fingerprint image signal S2, which is calculated according to a preset difference formula. The preset difference formula is:

[0035]

[0036] in: Used to represent the curved surface fingerprint image signal S1 sensed by the current curved surface fingerprint recognition sensor 1; Used to represent the background fingerprint image signal S0; Used to represent the inherent noise of the curved fingerprint recognition sensor 1; Used to indicate the valid signal of the currently sensed fingerprint image; It is used to represent the average value of multiple fingerprint image signals sensed multiple times previously; n is an integer greater than 1.

[0037] It can be understood that, for example, the signal collected by the curved fingerprint recognition sensor 1 is , that is, the currently sensed curved fingerprint image signal S1 is According to the characteristics of the curved fingerprint recognition sensor 1, The effective fingerprint signal will be variable The inherent noise signal of the curved fingerprint sensor 1 Together, that is If multiple fingerprint image signals are superimposed, that is , that is, the background fingerprint image signal is The curved fingerprint image signal currently sensed by the curved fingerprint recognition sensor 1 The current sensed curved fingerprint image signal minus the background fingerprint image signal is , that is, the preprocessing fingerprint image signal S2 can eliminate noise. In addition, since the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are both collected on the curved surface fingerprint recognition sensor 1, the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are identically distributed. Therefore, after the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are subtracted, data with good plane consistency and convenient for post-processing can be obtained.

[0038] like Figure 3 and Figure 4 As shown, Figure 3 The schematic diagram shows the effect of the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 in the same coordinate system. Figure 4 The schematic diagram shows the effect of subtracting the background fingerprint image signal S0 from the currently sensed curved fingerprint image signal S1. Figure 3 The effect of using two curves a1 and a2 with the same distribution of one-dimensional signals on the same coordinate system. Subtracting the two curves gives the distance between the curves. The distances between the curves with the same distribution are approximately equal, that is, the approximate straight line a3, such as Figure 4 As shown. Similarly, for two-dimensional image data, the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are collected from the same sensor, so the background fingerprint image signal S0 and the previously sensed fingerprint image signal S1 are identically distributed. After the background fingerprint image signal S0 and the previously sensed fingerprint image signal S1 are subtracted, the distance between the curved surfaces is obtained. Similarly, the distances between the identically distributed curved surface signals are approximately equal, that is, approximately flat. Therefore, the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 can be subtracted to obtain data with good plane consistency and convenient for post-processing.

[0039] In the above embodiment, after the currently sensed curved surface fingerprint image signal is planarized, the plane consistency is good, which is convenient for subsequent image processing. In addition, the currently sensed curved surface fingerprint image signal is planarized by subtracting the currently sensed curved surface fingerprint image signal from the background fingerprint image signal, and noise can be eliminated while the currently sensed curved surface fingerprint image signal is planarized, so that subsequent image processing, such as conversion, recognition, etc., is more accurate.

[0040] Please refer to Figure 5 , which is a flow chart of the method for producing the background fingerprint image signal S0. In this embodiment, the background fingerprint image signal S0 is preset during the production process. It can be understood that before step S101, the fingerprint image preprocessing method also includes the following steps.

[0041] Step S501, acquiring a fingerprint image signal sensed by the curved fingerprint recognition sensor 1.

[0042] Step S503, whether the number of times of acquiring fingerprint image signals reaches the preset number of times. When the number of times of sensing fingerprint images reaches the preset number of times, step S505 is executed. When the number of times of sensing fingerprint images does not reach the preset number of times, step S509 is executed. The preset number of times is but not limited to 8 to 20 times.

[0043] Step S505, average the multiple fingerprint image signals sensed multiple times to obtain the background fingerprint image signal S0. In this embodiment, the fingerprint image signals generated by the multiple sensing of the same fingerprint object can be obtained, which only requires one person to complete, making the production more convenient.

[0044] Step S507, storing the background fingerprint image signal S0.

[0045] Step S509, storing the sensed fingerprint image signal, and executing step S501.

[0046] In the above embodiment, the background fingerprint image signal is obtained by sensing the fingerprint image signal multiple times and averaging the multiple fingerprint image signals sensed multiple times, which is simple to operate.

[0047] It can be understood that the fingerprint image preprocessing method can be applied to the overall process of the fingerprint recognition method, and can also be applied to the process of processing sample fingerprint image signals or the process of verifying fingerprint images.

[0048] Please refer to Figure 6 , which is a flow chart of a fingerprint recognition method provided by the first embodiment using the fingerprint image preprocessing method. Specifically, the fingerprint image preprocessing method includes the following steps.

[0049] Step S601, obtaining a sample fingerprint image signal, where the sample fingerprint image signal is a curved surface fingerprint image signal.

[0050] Step S603, planarizing the sample fingerprint image signal to obtain a preprocessed sample fingerprint image signal. In this embodiment, planarizing the sample fingerprint image signal to obtain a preprocessed sample fingerprint image signal is the same as the planarizing method in the fingerprint image preprocessing method, which will not be repeated here.

[0051] Step S605: convert the preprocessed sample fingerprint image signal into a sample fingerprint image.

[0052] Step S607, obtaining a fingerprint image signal to be verified, where the fingerprint image signal to be verified is a curved surface fingerprint image signal.

[0053] Step S609, planarizing the fingerprint image signal to be verified to obtain a preprocessed fingerprint image signal to be verified. In this embodiment, planarizing the fingerprint image signal to be verified to obtain a preprocessed fingerprint image to be verified is the same as the planarizing method in the fingerprint image preprocessing method described above, and will not be repeated here.

[0054] Step S611, converting the pre-processed fingerprint image signal to be verified into a fingerprint image to be verified.

[0055] Step S613: Compare the fingerprint image to be verified with the sample fingerprint image to obtain a verification result.

[0056] In the above fingerprint recognition method, since both the sample fingerprint image signal and the fingerprint image signal to be verified are planarized, it is convenient to process and recognize the sample fingerprint image and the fingerprint image to be verified. Similarly, the above fingerprint recognition method adopts the planarization processing method in the fingerprint image preprocessing method, which can also remove noise, so that the fingerprint recognition process reduces noise interference and is more accurate.

[0057] Please see again Figure 2 , which is a functional program module diagram of the curved surface fingerprint recognition sensor 1 that applies the fingerprint image method provided in the first embodiment.

[0058] The curved surface fingerprint recognition sensor 1 comprises a sensing component 13, a detection module 14, a storage module 15, a pre-processing module 16, and a fingerprint recognition module 17. The sensing component 13 is provided with a curved surface sensing area 10.

[0059] The detection module 14 is used to obtain the currently sensed curved surface fingerprint image signal S1. It can be understood that the currently sensed curved surface fingerprint image signal S1 is a signal generated by the sensor component 13 caused by the finger object currently placed in the curved surface sensing area 10. At this time, the currently sensed curved surface fingerprint image signal S1 is distributed in a curved surface. In this embodiment, the sensor component 13 is a capacitive sensor.

[0060] The preprocessing module 16 is used to perform planarization processing on the currently sensed curved surface fingerprint image signal to obtain a preprocessed fingerprint image signal. Specifically, the currently sensed curved surface fingerprint image signal S1, which is distributed on a curved surface, is roughly distributed on a plane after planarization processing. In this embodiment, the planarization processing on the currently sensed curved surface fingerprint image signal S1 to obtain the preprocessed fingerprint image signal S2 is specifically: the difference between the currently sensed curved surface fingerprint image signal S1 and the background fingerprint image signal S0 is calculated to obtain the preprocessed fingerprint image signal S2. Among them, the background fingerprint image signal S0 is a fingerprint image signal formed by averaging multiple fingerprint image signals S sensed multiple times previously. The background fingerprint image signal S0 is stored in the storage module 16. In this embodiment, the background fingerprint image signal S0 is preset before leaving the factory. Furthermore, the multiple fingerprint image signals sensed multiple times previously are preferably collected for the same finger object, especially when the background fingerprint image signal S0 is set by the user. Collecting for the same finger object can ensure that the produced background fingerprint pattern S0 is more accurate. It can be understood that the finger object corresponding to the currently sensed curved fingerprint image signal S1 is different from the finger object corresponding to the fingerprint image signal S sensed multiple times in advance. In some feasible embodiments, the background fingerprint image signal S0 can also be set by the user. How to make the background fingerprint image signal S0 will be described in detail below.

[0061] Further, in this embodiment, the difference between the currently sensed curved surface fingerprint image signal S1 and the background fingerprint image signal S0 is calculated to obtain the preprocessed fingerprint image signal S2, which is calculated according to a preset difference formula. The preset difference formula is:

[0062]

[0063] in: Used to represent the curved surface fingerprint image signal S1 currently sensed by the curved surface fingerprint recognition sensor 1; Used to represent the background fingerprint image signal S0; Used to represent the inherent noise of the curved fingerprint recognition sensor 1; Used to indicate the valid signal of the currently sensed fingerprint image; It is used to represent the average value of multiple fingerprint image signals sensed multiple times previously; n is an integer greater than 1.

[0064] It can be understood that, for example, the signal collected by the curved fingerprint recognition sensor 1 is , that is, the currently sensed curved fingerprint image signal S1 is According to the characteristics of the curved fingerprint recognition sensor 1, The effective fingerprint signal will be variable The inherent noise signal of the curved fingerprint sensor 1 Together, that is If multiple fingerprint image signals are superimposed, that is , that is, the background fingerprint image signal is The curved fingerprint image signal currently sensed by the curved fingerprint recognition sensor 1 The current sensed curved fingerprint image signal minus the background fingerprint image signal is , that is, the preprocessing fingerprint image signal S2 can eliminate noise. In addition, since the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are both collected on the curved surface fingerprint recognition sensor 1, the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are identically distributed. Therefore, after the background fingerprint image signal S0 and the currently sensed curved surface fingerprint image signal S1 are subtracted, data with good plane consistency and convenient for post-processing can be obtained.

[0065] The fingerprint recognition module 17 is used to process and recognize the pre-processed fingerprint image signal S2. It can be understood that the pre-processed fingerprint image signal S2 can be a sample fingerprint image signal or a fingerprint image signal to be verified.

[0066] When the preprocessed fingerprint image signal S2 is a sample fingerprint image, the fingerprint recognition module 17 is used to convert the sample fingerprint image signal into a sample fingerprint image and store it in a sample fingerprint library (not shown). The sample fingerprint library can be stored in the storage module 15 or in another storage module, which is not limited here.

[0067] When the preprocessed fingerprint image signal S2 is a fingerprint image signal to be verified, the fingerprint recognition module 17 is used to convert the sample fingerprint image signal into a fingerprint image to be verified, and match the fingerprint image to be verified with the sample fingerprint images in the sample fingerprint library to obtain a verification result.

[0068] Please refer to Figure 7, which is a schematic diagram of the internal structure of the fingerprint recognition sensor 1. The fingerprint recognition sensor 1 includes a storage medium 11 and a processor 12. The storage medium 11 is used to store fingerprint recognition program instructions. The processor 12 is used to execute the fingerprint recognition program instructions to implement the above-mentioned fingerprint recognition method, which is the same as the above-mentioned fingerprint recognition methods and will not be repeated here.

[0069] Figure 7 Only the fingerprint recognition sensor 1 having the components 11 and 12 is shown. It can be understood by those skilled in the art that Figure 7 The structure shown does not constitute a limitation on the fingerprint recognition sensor 1 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0070] Please refer to Figure 7 and Figure 8 , the fingerprint recognition sensor 1 is applied to the electronic device 100. The electronic device 100 may be a mobile phone, a tablet computer, a laptop computer, a door access control system, etc. In this embodiment, the specific application of the fingerprint recognition sensor 1 is described by taking the electronic device 100 as a mobile phone as an example. The electronic device 100 includes a main body 1001. The main body 1001 includes a front face 1002, a back face 1003, and a side face 1004 located between the front face 1002 and the back face 1003. The sensing area 10 of the fingerprint recognition sensor 1 is arranged on the side face 1004 of the main body 1001. Preferably, the side face 1004 is provided with a button having an arc-shaped top surface (not shown in the figure), and the sensing area 10 is arranged on the arc-shaped top surface of the button. In some feasible embodiments, the sensing area 10 can also be arranged at other positions of the electronic device 100, which is not limited here. It can be understood that when the electronic device is other electronic products, the position of the sensing area 10 can be changed according to the actual design. For example, when the electronic device 100 is a door access control system, the fingerprint recognition sensor 1 can be arranged at the bottom of the door access control system.

[0071] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A fingerprint image preprocessing method, the fingerprint image preprocessing method is applied to a curved surface fingerprint recognition sensor, the curved surface fingerprint recognition sensor includes a curved surface sensing area for placing a finger, characterized in that: The fingerprint image preprocessing method comprises: Acquire the currently sensed curved surface fingerprint image signal; and The planarization process is performed on the currently sensed curved surface fingerprint image signal to obtain a preprocessed fingerprint image signal, comprising: calculating the difference between the currently sensed curved surface fingerprint image signal and a background fingerprint image signal to obtain the preprocessed fingerprint image signal, wherein the background fingerprint image signal is a fingerprint image signal formed by averaging a plurality of fingerprint image signals sensed multiple times previously.

2. The fingerprint image preprocessing method according to claim 1, characterized in that: Calculating the difference between the currently sensed curved surface fingerprint image signal and the background fingerprint image signal to obtain a preprocessed fingerprint image signal, specifically including: The difference between the currently sensed curved surface fingerprint image signal and the background fingerprint image signal is calculated according to a preset difference formula, wherein the preset difference formula is: Where: G(χ n+1 ) is used to represent the currently sensed curved fingerprint image signal; is used to represent the background fingerprint image signal; Φ is used to represent the inherent noise of the curved fingerprint recognition sensor; f(χ n+1 ) is used to represent the valid signal of the currently sensed fingerprint image; It is used to represent the average value of multiple fingerprint image signals sensed multiple times previously, and n is an integer greater than 1.

3. The fingerprint image preprocessing method according to claim 1, characterized in that: Before acquiring the currently sensed curved surface fingerprint image signal, the fingerprint image preprocessing method further includes: sensing a fingerprint image signal, wherein the fingerprint image signal is a curved surface fingerprint image signal; Whether the fingerprint image signal is sensed to reach a preset number of times; When the fingerprint image is sensed for a preset number of times, the plurality of fingerprint image signals sensed multiple times are averaged to obtain the background fingerprint image signal; and The background fingerprint image signal is stored.

4. The fingerprint image preprocessing method according to claim 3, characterized in that: The preset number of times is 8 to 20 times.

5. The fingerprint image preprocessing method according to claim 1, characterized in that: The finger object corresponding to the currently sensed fingerprint image is different from the finger objects corresponding to the fingerprint images sensed multiple times in advance.

6. The fingerprint image preprocessing method according to claim 5, characterized in that: The fingerprint images sensed in advance for multiple times correspond to the same finger object.

7. A fingerprint recognition method, the fingerprint recognition method is applied to a curved surface fingerprint recognition sensor, the curved surface fingerprint recognition sensor includes a curved surface sensing area for placing a finger, characterized in that: The fingerprint recognition method comprises: Acquire a sample fingerprint image signal, wherein the sample fingerprint image signal is a curved surface fingerprint image signal; The sample fingerprint image signal is subjected to planarization processing to obtain a preprocessed sample fingerprint image signal, comprising: calculating the difference between the sample fingerprint image signal and a background fingerprint image signal to obtain the preprocessed sample fingerprint image signal, wherein the background fingerprint image signal is a fingerprint image signal formed by averaging a plurality of fingerprint image signals sensed multiple times previously; and The preprocessed sample fingerprint image signal is converted into a sample fingerprint image.

8. The fingerprint recognition method according to claim 7, characterized in that: The fingerprint recognition method comprises: Acquire a fingerprint image signal to be verified, wherein the fingerprint image signal to be verified is a curved surface fingerprint image signal; Performing planarization processing on the fingerprint image signal to be verified to obtain a preprocessed fingerprint image signal to be verified; Converting the pre-processed fingerprint image signal to be verified into a fingerprint image to be verified; and The fingerprint image to be verified is compared with the sample fingerprint image to obtain a verification result.

9. The fingerprint recognition method according to claim 8, characterized in that: The planarization process is performed on the fingerprint image signal to be verified to obtain a preprocessed fingerprint image signal to be verified, specifically comprising: The difference between the fingerprint image signal to be verified and the background fingerprint image signal is calculated to obtain the preprocessed fingerprint image signal to be verified.

10. A curved fingerprint recognition sensor, characterized in that: The curved fingerprint recognition sensor comprises: A storage medium for storing fingerprint recognition program instructions; and A processor, configured to execute the fingerprint recognition program instructions to implement the fingerprint recognition method according to any one of claims 7 to 9.

11. An electronic device, characterized in that: The electronic device includes a main body and the curved fingerprint recognition sensor as claimed in claim 10 arranged on the main body.

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