Fingerprint processing method, device and electronic equipment

Abstract

The disclosed embodiments provide a fingerprint processing method, device, and electronic device. The fingerprint processing method includes: during fingerprint template registration, collecting fingerprint data at a first frame rate via a fingerprint sensor, each frame of fingerprint data including multiple sub-data of different phases, at least two of the multiple sub-data of different phases being collected based on the same configuration; comparing the difference between two sub-data of different phases collected based on the same configuration to obtain the motion blur of the frame of fingerprint data; and registering the fingerprint template based on the motion blur of the frame of fingerprint data. The disclosed embodiments allow the finger to continuously contact and move with the fingerprint collection area during fingerprint template registration, rather than being limited to repeated pressing and lifting of the hand. This improves user input flexibility during fingerprint template registration, improves fingerprint template registration efficiency, and ensures the quality of the registered fingerprint template.

Description

Technical Field

[0001] The present disclosure relates to the field of fingerprint recognition technology, and in particular to a fingerprint processing method, device and electronic device. Background Art

[0002] Ultrasonic fingerprint recognition systems generate fingerprint images by transmitting and receiving ultrasonic signals. By combining the differences in acoustic impedance between the screen, finger, and air, they distinguish the valleys and ridges on the fingerprint, thereby capturing fingerprint features for identification. During application, the fingerprint pattern must first be captured as a template for identification, so the fingerprint template plays a significant role in identification.

[0003] In the related art, the fingerprint position of the finger is collected and registered as a template by repeatedly pressing and lifting the hand. During the fingerprint template registration process, the user is required to repeatedly place the finger on the fingerprint sensor. After each placement, the user is required to lift the finger and adjust the finger position so that the other position of the finger contacts the fingerprint sensor when the finger is placed on the fingerprint sensor again. This repeated pressing and lifting method is inefficient and results in a longer fingerprint template registration process. In addition, if the finger moves during the pressing process, the fingerprint image will be distorted due to the movement, making the registered fingerprint template significantly different from the actual fingerprint, affecting the final fingerprint recognition performance. Summary of the Invention

[0004] In view of the above problems, the embodiments of the present disclosure provide a fingerprint processing method, device, and electronic device to at least partially solve the above technical problems.

[0005] In a first aspect, an embodiment of the present disclosure provides a fingerprint processing method, comprising: during a fingerprint template registration process, collecting fingerprint data through a fingerprint sensor at a first frame rate, each frame of fingerprint data including multiple sub-data of different phases, at least two of the multiple sub-data of different phases being collected based on the same configuration; comparing the difference between two sub-data of different phases collected based on the same configuration to obtain the motion blur of the frame fingerprint data; and performing fingerprint template registration based on the motion blur of the frame fingerprint data.

[0006] Optionally, the difference between the two sub-data of different phases collected based on the same configuration is compared to obtain the motion blur of the frame fingerprint data, including: determining a difference map between the two sub-data of different phases collected based on the same configuration; determining the discreteness of the difference map in the spatial domain; and determining the motion blur of the frame fingerprint data based on the discreteness.

[0007] Optionally, the method further includes: determining a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; the above-mentioned determination of the motion blur of the frame fingerprint data based on the discreteness includes: determining the signal amount of the candidate fingerprint image; normalizing the discreteness based on the signal amount to obtain the motion blur of the frame fingerprint data.

[0008] Optionally, the method further includes: determining a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; the above-mentioned comparison between the difference between two sub-data of different phases collected based on the same configuration to obtain the motion blur of the frame fingerprint data, and further includes: determining the image quality score of the candidate fingerprint image; adjusting the motion blur according to the image quality score, wherein the motion blur is negatively correlated with the image quality score.

[0009] Optionally, the above-mentioned adjusting the motion blur according to the image quality score includes: comparing the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; and adjusting the motion blur according to a ratio corresponding to the image quality score interval.

[0010] Optionally, if the image quality score is greater than or equal to a first score threshold, the motion blur is reduced according to a first ratio; if the image quality score is less than the first score threshold and greater than or equal to a second score threshold, the motion blur is reduced according to a second ratio, and the first ratio is greater than the second ratio; if the image quality score is less than the second score threshold, the motion blur is kept unchanged.

[0011] Optionally, the above-mentioned fingerprint template registration based on the motion blur of the frame fingerprint data includes: classifying the frame fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data, the motion blur type including a non-blurred type and a fully blurred type; and registering the fingerprint template according to the motion blur type of the frame fingerprint data.

[0012] Optionally, the above-mentioned classification of the frame fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data includes: if the motion blur is less than or equal to a first motion blur threshold, determining that the motion blur type of the frame fingerprint data is a non-blurred type; if the motion blur is greater than the first motion blur threshold and less than or equal to a second motion blur threshold, determining that the motion blur type of the frame fingerprint data is a semi-blurred type; if the motion blur is greater than the second motion blur threshold, determining that the motion blur type of the frame fingerprint data is a fully blurred type.

[0013] Optionally, the above also includes: determining a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; the above fingerprint template registration based on the motion blur type of the frame fingerprint data includes: the type of the fingerprint image is a semi-blurred type or a non-blurred type, and judging whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image.

[0014] Optionally, the above-mentioned determination of whether to register a candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image includes: detecting whether the effective area of the candidate fingerprint image is greater than an area threshold; if the effective area of the candidate fingerprint image is greater than the area threshold, detecting whether the image quality score of the candidate fingerprint image is greater than a third score threshold; if the image quality score of the candidate fingerprint image is greater than the third score threshold, registering the candidate fingerprint image as a fingerprint template.

[0015] Optionally, the above-mentioned fingerprint template registration based on the motion blur type of the frame fingerprint data includes: if the motion blur type of the frame fingerprint data is a non-blur type, registering a first type of fingerprint template based on the frame fingerprint data; if the motion blur type of the frame fingerprint data is a semi-blur type, registering a second type of fingerprint template based on the frame fingerprint data.

[0016] Optionally, the second type of fingerprint template is used to assist the first type of fingerprint template in fingerprint matching.

[0017] Optionally, the above method also includes: determining whether the number of registered first-class fingerprint templates reaches a threshold; if the number of registered first-class fingerprint templates reaches the threshold, ending the fingerprint template registration; if the number of registered first-class fingerprint templates does not reach the threshold, continuing the above step of collecting fingerprint data through the fingerprint sensor at the first frame rate.

[0018] Optionally, the above method further includes: during the fingerprint recognition process, collecting fingerprint data through the fingerprint sensor at a second frame rate, wherein the first frame rate is greater than the second frame rate.

[0019] Optionally, the fingerprint template registration process includes a process in which the finger is in continuous contact with the fingerprint collection area and moves, and the movement is used to change the fingerprint position where the finger is in contact with the fingerprint collection area.

[0020] Optionally, the fingerprint sensor includes an ultrasonic fingerprint sensor.

[0021] In a second aspect, an embodiment of the present disclosure further provides a fingerprint processing device, comprising: an acquisition module, for acquiring fingerprint data at a first frame rate through a fingerprint sensor during a fingerprint template registration process, wherein each frame of fingerprint data includes multiple sub-data of different phases, and at least two of the multiple sub-data of different phases are acquired based on the same configuration; a registration module, for comparing the difference between two sub-data of different phases acquired based on the same configuration to obtain the motion blur of the frame fingerprint data; and performing fingerprint template registration according to the motion blur of the frame fingerprint data.

[0022] Optionally, the registration module is configured to determine a difference map between two sub-data of different phases acquired based on the same configuration, determine a discreteness of the difference map in a spatial domain, and determine a motion blur of the frame fingerprint data according to the discreteness.

[0023] Optionally, the registration module is further used to determine a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; and the registration module is used to determine the signal amount of the candidate fingerprint image; and normalize the discreteness based on the signal amount to obtain the motion blur of the frame fingerprint data.

[0024] Optionally, the registration module is further used to determine a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; and the registration module is used to determine an image quality score of the candidate fingerprint image; and adjust the motion blur according to the image quality score, wherein the motion blur is negatively correlated with the image quality score.

[0025] Optionally, the registration module is configured to compare the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; and adjust the motion blur according to a ratio corresponding to the image quality score interval.

[0026] Optionally, the registration module is used to classify the frame fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data, where the motion blur type includes a non-blurred type and a fully blurred type; and register the fingerprint template according to the motion blur type of the frame fingerprint data.

[0027] Optionally, the registration module is used to determine that the motion blur type of the frame fingerprint data is a non-blur type if the motion blur is less than or equal to a first motion blur threshold; if the motion blur is greater than the first motion blur threshold and less than or equal to a second motion blur threshold, determine that the motion blur type of the frame fingerprint data is a semi-blur type; if the motion blur is greater than the second motion blur threshold, determine that the motion blur type of the frame fingerprint data is a full-blur type.

[0028] Optionally, the registration module is further used to determine a candidate fingerprint image for registration as a fingerprint template based on the frame fingerprint data; and the registration module is used to determine whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image if the type of the fingerprint image is a semi-blurred type or a non-blurred type.

[0029] Optionally, the registration module is configured to register a first type of fingerprint template based on the frame fingerprint data if the motion blur type of the frame fingerprint data is a non-blur type; and to register a second type of fingerprint template based on the frame fingerprint data if the motion blur type of the frame fingerprint data is a semi-blur type.

[0030] In a third aspect, an embodiment of the present disclosure further provides an electronic device, including: a fingerprint sensor; and the above-mentioned fingerprint processing device.

[0031] In a fourth aspect, an embodiment of the present disclosure further provides an electronic device, comprising: a processor; and a memory for storing a program, wherein the program comprises instructions, which, when executed by the processor, enable the processor to execute the above-mentioned method of the embodiment of the present disclosure.

[0032] In a fifth aspect, an embodiment of the present disclosure further provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the above-mentioned method of the embodiment of the present disclosure.

[0033] The fingerprint processing method, apparatus, and electronic device provided by the embodiments of the present disclosure, during the fingerprint template registration process, each frame of fingerprint data collected includes multiple sub-data of different phases, at least two of the multiple sub-data of different phases are collected based on the same configuration, and the motion blur of the frame of fingerprint data is obtained by comparing the difference between the two sub-data of different phases collected based on the same configuration. The fingerprint template is registered based on the motion blur of the frame of fingerprint data, which can at least partially avoid registering a fingerprint image that is distorted and deformed due to the influence of finger movement as a fingerprint template. The fingerprint template registration process allows the finger to continuously contact and move with the fingerprint collection area without being limited to a repeated press-and-raise method. This can improve the flexibility of user input in fingerprint template registration, improve the efficiency of fingerprint template registration, and ensure the quality of the registered fingerprint template.

[0034] These and other aspects of the present disclosure will become more apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1A A schematic diagram showing an electronic device to which an exemplary embodiment of the present disclosure may be applied is shown.

[0037] Figure 1B A schematic diagram illustrating another electronic device to which an exemplary embodiment of the present disclosure may be applied is shown.

[0038] Figure 1C A system block diagram illustrating an electronic device to which exemplary embodiments of the present disclosure may be applied.

[0039] Figure 2 A flowchart of a fingerprint processing method according to an exemplary embodiment of the present disclosure is shown.

[0040] Figure 3 A flowchart of a motion blur determination method according to an exemplary embodiment of the present disclosure is shown.

[0041] Figure 4 A flowchart of a method for registering a fingerprint template according to motion blur according to an exemplary embodiment of the present disclosure is shown.

[0042] Figure 5 A structural block diagram of a fingerprint processing device according to an exemplary embodiment of the present disclosure is shown.

[0043] Figure 6 A structural block diagram of an ultrasonic fingerprint processing system according to an exemplary embodiment of the present disclosure is shown.

[0044] Figure 7 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0045] The embodiments of the present disclosure are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure and are not to be construed as limiting the present disclosure.

[0046] In order to enable those skilled in the art to better understand the solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present disclosure.

[0047] In the embodiments of the present disclosure, it should be noted that, in this document, relational terms such as first and second, etc., are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0048] Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0049] In the description of the embodiments of the present disclosure, words such as "example" or "for example" are used to indicate an example, illustration, or description. Any embodiment or design described as "example" or "for example" in the embodiments of the present disclosure is not to be construed as being preferred or having more advantages than another embodiment or design. The use of words such as "example" or "for example" is intended to clearly present relative concepts.

[0050] In addition, "plurality" in the embodiments of the present disclosure refers to two or more. In view of this, in the embodiments of the present disclosure, "plurality" can also be understood as "at least two." "At least one" can be understood as one or more, for example, one, two, or more. For example, "including at least one" means including one, two, or more, and does not limit which ones are included. For example, "including at least one of A, B, and C" can mean including A, B, C, A and B, A and C, B and C, or A, B, and C.

[0051] It should be noted that in the embodiments of the present disclosure, "and / or" describes the association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / ", unless otherwise specified, generally indicates that the associated objects are in an "or" relationship.

[0052] Figure 1A and Figure 1B Schematic diagram of an electronic device in which various schemes described herein may be implemented according to an exemplary embodiment of the present disclosure is shown. Figure 1A and Figure 1B As shown, the electronic device 100 may include a device body 101 and a fingerprint sensor 102. The fingerprint sensor 102 can capture fingerprint images for fingerprint recognition. The fingerprint sensor 102 may include, but is not limited to, a capacitive fingerprint sensor, an optical fingerprint sensor, an ultrasonic fingerprint sensor, etc., and the specific location of the fingerprint sensor 102 in the electronic device 100 may be set on the side, back, front, or below the display screen of the device body 101 according to actual product design requirements.

[0053] In some embodiments, the electronic device 100 may be a portable electronic device, such as a smartphone, a tablet computer, a laptop computer, a personal digital assistant, etc. In other embodiments, the electronic device 100 may also be a smart wearable device, and the disclosed embodiments do not limit the type of the electronic device 100.

[0054] In some embodiments, the fingerprint sensor 102 can be specifically set on the side of the device body 101 of the electronic device 100; as smartphones or other portable electronic devices develop towards being lighter or foldable, the thickness of the electronic device 100 is getting smaller and smaller, which causes the fingerprint sensor 102 set on the side of the device body 101 to become narrower and narrower.

[0055] See also Figure 1A In a typical embodiment, the device body 101 includes a display screen 10 and a middle frame 20. The display screen 10 is located on the front of the device body 101, displaying images and providing a user interface. The middle frame 20 is generally located between the display screen 10 and the back cover of the electronic device, supporting the display screen 10 and housing various functional components within the device body 101, such as the motherboard, battery, camera, speaker, microphone, and various sensor units. In a specific embodiment, the middle frame 20 includes a frame located around the periphery of the device body 101. The frame may include multiple sides and may carry a power button, volume button, or other function buttons. The fingerprint sensor 102 may be located on one of the sides of the frame and have a sensing area 108. In a specific embodiment, the fingerprint sensor 102 may be a fingerprint recognition chip or a fingerprint module having a fingerprint recognition chip. It may be integrated above the power button or volume button on the side of the frame, embedded in a predetermined area on the side of the frame, or attached to the inner surface of the side of the frame to allow the user to input a fingerprint and implement the side fingerprint function of the electronic device 100.

[0056] In some embodiments, the fingerprint sensor 102 can be specifically arranged below the display screen of the electronic device 100, which is located on the front of the device body 101 and is used to display images and provide a human-computer interaction interface for the user. Compared with the fingerprint sensor 102 being arranged in an area outside the display screen on the front of the device body, the fingerprint sensor 102 is arranged below the display screen of the electronic device 100, which can increase the screen-to-body ratio of the electronic device. The fingerprint sensor 102 uses ultrasonic, optical and other penetrating technologies inside the screen to penetrate various materials, transmit ultrasonic signals or optical signals to the outer surface of the display screen, and receive reflected signals reflected by the finger to realize fingerprint image acquisition for fingerprint recognition.

[0057] See also Figure 1B , as another typical embodiment, with Figure 1A The difference between the embodiments is that the fingerprint sensor 102 is arranged below the display screen 10, that is, inside the display screen 10. The display screen 10 comprises, from top to bottom, a cover glass 11, a touchpad 12, and a display panel 13. The fingerprint sensor 102 can be arranged below the display panel 13. The fingerprint sensor 102 has a sensing area 108. The area on the display screen 10 corresponding to the sensing area 108 is the fingerprint collection area. Usually, a visual prompt can be displayed on the fingerprint collection area on the screen 10 to inform the user of the location of the fingerprint collection area. The fingerprint sensor 102 can transmit a signal using ultrasonic, optical or other penetrating technologies so that the signal penetrates the cover glass 11, the touchpad 12, the display panel 13, etc. The signal can be reflected by a finger on the outer surface of the cover glass 11 to form a reflected signal. The reflected signal penetrates the cover glass 11, the touchpad 12, the display panel 13, etc. to reach the sensing area 108 of the fingerprint sensor 102. The fingerprint sensor 102 generates a fingerprint image based on the reflected signal.

[0058] Please also refer to Figure 1C The fingerprint sensor 102 includes a sensing array 103, an output module 104, an interface module 105, and a driver module 106. The sensing array 103 is configured to couple with the user's finger to collect fingerprint information when the user presses the fingerprint sensor 102 to input a fingerprint. Specifically, the sensing array 103 includes a plurality of sensing electrodes distributed in an array. The area where the sensing array 103 is located, or its effective fingerprint collection area, constitutes the sensing area 108 of the fingerprint sensor 102. The driver module 106 and the output module 104 are connected to the sensing array 103 and the interface module 105, respectively. The driver module 106 is configured to drive the sensing array 103 to perform fingerprint scanning to collect fingerprint information from the user's finger. The output module 104 is configured to generate corresponding fingerprint data based on the fingerprint information collected by the sensing array 103 and output the fingerprint data to the control system 120 via the interface module 105. The interface module 105 can be specifically a serial peripheral interface (SPI).

[0059] Continue reading Figure 1C , the control system 120 may include one or more general-purpose single-chip or multi-chip processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or combinations thereof. According to some examples, the control system 120 may include dedicated components for controlling the fingerprint sensor 102. In some implementations, the functionality of the control system 120 may be divided between one or more controllers or processors, such as between a dedicated sensor controller and an application processor of an electronic device. Reference Figure 1C , the control system 120 may include an application processor 121 of the electronic device. The application processor 121 may be specifically a central processing unit (CPU) or other processing unit or control unit with processing capabilities inside the electronic device 100, such as a microcontroller (MCU), which is connected to the interface module 105 and includes a fingerprint processing device, which is mainly used to control the working state of the fingerprint sensor 102, process the fingerprint data output by the fingerprint sensor 102, and perform fingerprint template registration and fingerprint matching verification to determine whether the currently collected fingerprint image is a legitimate fingerprint, and unlock the electronic device 100 or perform other functions related to fingerprint recognition based on the judgment result.

[0060] Fingerprint recognition typically consists of a fingerprint template registration phase and a fingerprint verification phase. During the fingerprint template registration phase, the user's input fingerprint is collected to form a fingerprint template. During the fingerprint verification phase, the user's input fingerprint is collected to obtain a query fingerprint image. The query fingerprint image is then matched against the registered fingerprint template to verify whether the query fingerprint image is a legitimate fingerprint. To reduce the false rejection rate, multiple templates corresponding to the finger image are obtained during the fingerprint template registration phase. See Figure 1A The fingerprint sensor 102 is narrow, so the fingerprint position it can capture is small. That is, one fingerprint image represents a small fingerprint position on the finger. The fingerprint position of the user on the fingerprint sensor 102 varies. Therefore, it is necessary to capture fingerprint images multiple times for fingerprint template registration to obtain multiple templates in order to reduce the false rejection rate of fingerprint recognition. Figure 1B The fingerprint sensor 102 under the screen can have a large sensing area. Due to the influence of the user's pressing habits, the position of the user's fingerprint on the fingerprint sensor 102 is also relatively variable. Therefore, it is necessary to collect fingerprint images multiple times for fingerprint template registration to obtain multiple templates in order to reduce the false rejection rate of fingerprint recognition.

[0061] To obtain multiple templates, during the fingerprint template registration process, the user is required to repeatedly place their finger on the fingerprint sensor. After each placement, the user is required to lift their finger and adjust the finger position so that when the finger is placed on the fingerprint sensor again, other positions of the finger will contact the fingerprint sensor, thereby registering multiple fingerprint templates at multiple positions of the finger. This repeated pressing and lifting method is inefficient and results in a longer fingerprint template registration process. In addition, if the finger moves during the pressing process, the fingerprint image will be distorted due to the movement, causing the registered fingerprint template to differ significantly from the actual fingerprint, affecting the final fingerprint recognition performance.

[0062] The present disclosure provides a fingerprint processing method, which can be applied to Figure 1A 、 Figure 1B The electronic device 100 shown is used to improve the fingerprint template registration experience.

[0063] Figure 2 A flow chart of a fingerprint processing method according to an exemplary embodiment of the present disclosure is shown. Figure 2 As shown, the fingerprint processing method of the embodiment of the present disclosure can be applied to the fingerprint template registration stage, and can at least partially avoid registering a fingerprint image that is distorted and deformed due to the influence of finger movement as a fingerprint template, so that the finger can continuously contact and move with the fingerprint collection area during the fingerprint template registration process, without being limited to repeated pressing and lifting of the hand. It can improve the user input flexibility in fingerprint template registration, improve the fingerprint template registration efficiency and ensure the quality of the registered fingerprint template, which specifically includes the following steps.

[0064] Step S201 : During fingerprint template registration, fingerprint data is collected by a fingerprint sensor at a first frame rate. Each frame of fingerprint data includes a plurality of sub-data at different phases, and at least two of the plurality of sub-data at different phases are collected based on the same configuration.

[0065] In an embodiment of the present disclosure, in the electronic device 100, the fingerprint sensor 102 can start the fingerprint collection function upon detecting contact of a user's finger or according to the instruction of the application processor 121 of the electronic device 100, and collect the fingerprint information input by the user by pressing the fingerprint sensor 102 through its sensing array 103, and generate a fingerprint image based on the fingerprint information input by the user.

[0066] For example, when fingerprint sensor 102 is a capacitive fingerprint sensor, the multiple sensing electrodes of the sensing array 103 form different coupling capacitances with the ridges and valleys of the user's finger. By driving the sensing array 103 to detect the capacitance signals formed by the ridges and valleys and the sensing electrodes, fingerprint sensor 102 can collect fingerprint information from the portion of the user's finger pressed against sensing area 108 and generate a fingerprint image based on this fingerprint information. This fingerprint image is specifically a digital image formed by integrating the fingerprint information at the corresponding position of the finger collected by all the sensing electrodes of the sensing array 103. Fingerprint sensor 102 can also perform some processing on the generated fingerprint image and temporarily store the fingerprint image internally, pending access by application processor 121 of electronic device 100.

[0067] For example, if fingerprint sensor 102 is an ultrasonic fingerprint sensor, the ultrasonic transmitter of fingerprint sensor 102 transmits an ultrasonic signal. The ultrasonic signal passes through the surface of the skin and is reflected by the ridges and valleys of the fingerprint. The ridges reflect more ultrasonic energy, while the valleys reflect less energy. The ultrasonic receiver of fingerprint sensor 102 receives the echo signal and converts it into an electrical signal indicating the reflected ultrasonic energy. This signal can then capture fingerprint information from the portion of the user's finger pressed against sensing area 108 and generate a fingerprint image based on this fingerprint information. In some implementations, the ultrasonic transmitter of fingerprint sensor 102 can include a piezoelectric transmitter layer. The ultrasonic wave is generated by applying a voltage to the piezoelectric transmitter layer, causing it to expand or contract according to an applied signal. Referring to FIG1B , the ultrasonic wave generated by the transmitter layer penetrates display panel 13, touchpad 12, cover glass 11, and the like and is reflected by the ridges and valleys of the fingerprint. The ultrasonic receiver of the fingerprint sensor 102 may include a piezoelectric receiver layer and an array of pixel circuits, each pixel circuit being configured to convert charge generated in the piezoelectric receiver layer proximate to the pixel circuit into an electrical signal. Each pixel circuit may include a pixel input electrode coupling the piezoelectric receiver layer to the pixel circuit.

[0068] In an embodiment of the present disclosure, in the electronic device 100, the application processor 121 can enter a fingerprint template registration process in response to a user operation to obtain multiple fingerprint templates. When entering the fingerprint template registration process, the application processor 121 can connect to the interface module 105 and send instructions to the fingerprint sensor 102 through the interface module 105, causing the fingerprint sensor to collect fingerprint data at a first frame rate for fingerprint template registration. Each frame of fingerprint data can be transmitted to the application processor 121 via the interface module 105.

[0069] In an embodiment of the present disclosure, in the electronic device 100, the application processor 121 may further display a visual prompt through the display screen 10 during the fingerprint template registration process. The visual prompt may include a prompt about the fingerprint template registration operation mode. As a typical implementation, the user may be prompted to press the finger on the fingerprint sensor 102 and move the finger while maintaining the pressure, so that different fingerprint positions on the finger are pressed to the fingerprint sensor 102, thereby allowing the fingerprint sensor 102 to collect fingerprint images of multiple fingerprint positions. It should be understood that the embodiments of the present disclosure are not limited to the method of continuous pressing and moving, but may also be a combination of continuous pressing and moving and pressing-lifting, or only repeated pressing-lifting. Reference Figure 1B As shown, the visual prompt may also include a prompt indicating the location of the fingerprint collection area. During the fingerprint template registration process, the visual prompt may also include registered fingerprint positions and unregistered fingerprint positions, so that the user can move his finger to allow the fingerprint sensor 102 to collect fingerprint images of unregistered fingerprint positions.

[0070] In the embodiment of the present disclosure, in the electronic device 100, the application processor 121 can control the fingerprint sensor 102 to collect fingerprint data according to the first frame rate during the fingerprint template registration process. Figure 1B When a finger is pressed against the fingerprint collection area on the display screen 10 and moves, to improve the overall registration experience and reduce registration time, the application processor 121 can set a higher first frame rate. The first frame rate during fingerprint template registration is higher than the second frame rate during fingerprint recognition. As a typical example, the application processor 121 can set the first frame rate during fingerprint template registration to approximately 60 Hz to 100 Hz, and the second frame rate during fingerprint recognition to 10 Hz. Furthermore, the first and second frame rates can be set according to actual product design requirements.

[0071] In the embodiments of the present disclosure, the difference between two sub-data of different phases collected based on the same configuration in each frame of fingerprint data can reflect the motion state of the finger when the frame of fingerprint data was collected. The finger motion state affects whether the fingerprint image is distorted and the degree of distortion. Therefore, step S202 can be performed to compare the difference between the two sub-data of different phases collected based on the same configuration to obtain the motion blur of the frame of fingerprint data. Motion blur refers to the phenomenon of deformation, distortion, and smearing of the fingerprint pattern during the movement of the finger, which may cause the collected fingerprint pattern to not match the actual fingerprint pattern. Motion blur can measure the possibility and degree of this phenomenon caused by finger movement.

[0072] Furthermore, in embodiments of the present disclosure, a final fingerprint image can be generated based on at least some of the sub-data at multiple different phases within a frame of fingerprint data. This final fingerprint image is a candidate fingerprint image for registration as a fingerprint template during the fingerprint template registration process. In electronic device 100, application processor 121 can perform processing such as fusion on the multiple sub-data at different phases to obtain the final fingerprint image.

[0073] As an embodiment, in the electronic device 100, the application processor 121 can control the fingerprint sensor 102 to collect sub-data of at least two phases. Specifically, when the fingerprint sensor 102 is an ultrasonic sensor, by adjusting the time interval of the fingerprint sensor 102 transmitting ultrasonic waves, the phase of the received reflected wave can be controlled to obtain multiple sub-data of multiple phases at multiple time points. For example, at the t1th moment of the frame F1, the sub-data of the phase P1 is obtained, at the t2th moment, the sub-data of the phase P2 is obtained, at the t3th moment, the sub-data of the phase P3 is obtained, and so on, at the t4th moment, the sub-data of the phase P4 is obtained. i Get phase P at the moment i The sub-data of i phase at time point i is obtained. i+1 At this moment, the phase P is obtained i+1 Sub-data of t1 and t i+1 The time interval is the longest, which can better reflect the finger movement state. Phase P1 and phase P i+1 The sub-data of is collected based on the same configuration. i+1 During this period, the finger has basically no movement, so the two sub-data are basically the same. If i+1 If the finger moves during this period, the difference between the two sub-data is positively correlated with the movement state of the finger. i+1 The motion blur of a frame of fingerprint data is obtained by comparing the sub-data.

[0074] As an example, in electronic device 100, a fingerprint image at any phase can be generated in the following manner. Specifically, the fingerprint sensor 102 is controlled to transmit an ultrasonic signal corresponding to the phase. The receiver array of fingerprint sensor 102 detects the reflected signal formed by reflection from the finger and converts it into an electrical signal. Each receiver in the receiver array of fingerprint sensor 102 corresponds to a specific spatial location and records the reflected signal at that location. The application processor 121 (or a separately provided analog-to-digital converter, etc.) can convert the electrical signal into a digital signal, which can then be further converted into a processable digital format. Because ultrasonic waves propagate at different speeds in different media, the received signals will have different phase offsets. The application processor 121 can perform phase correction on these signals to ensure the correct phase relationship between the signals. For each receiver, the corrected signal is integrated over time to enhance the signal and reduce noise. The integration can be a simple time summation or a weighted integration, where the weights may be related to the phase or amplitude of the signal. Using the integrated signals, a fingerprint image at each receiver location can be reconstructed. This typically involves a back-projection algorithm or beamforming technique, which projects the signal back onto the finger surface to form a two-dimensional or three-dimensional fingerprint image. In the embodiment of the present disclosure, when generating the first fingerprint image and the second fingerprint image of the predetermined phase, the phase offset used for phase correction and the integration time used for integration are substantially the same, so that the processing methods of the two are substantially the same.

[0075] Continuing with the above embodiment, the above t1 to t i The obtained multi-phase sub-data is fused to highlight fingerprint features and suppress noise. During the fingerprint template registration process, the candidate fingerprint image for registration as a fingerprint template is obtained through fusion. The fusion method can be a simple summation, weighted averaging, or a more complex image processing algorithm, which is not limited in the present embodiment.

[0076] In the above implementation, theoretically, the greater the number of phases, the more accurate the final fingerprint image generated based on the multi-phase fingerprint image. However, the more phases, the longer it takes to generate a frame of fingerprint data, which affects the frame rate. Considering the significant impact of sliding registration on the frame rate, some performance can be sacrificed by using fewer phases. As a typical implementation, a frame of fingerprint data includes fingerprint images from two phases, Phase 0 and Phase 1, plus a fingerprint image from Phase 2 with the same configuration as Phase 0, for a total of three fingerprint images from three phases at three time points. It should be understood that in specific implementations, the number of phases can be adjusted based on actual product design needs to meet design requirements for frame rate and fingerprint image quality.

[0077] Step S202 : comparing the difference between two sub-data collected at different phases based on the same configuration to obtain the motion blur of the frame fingerprint data.

[0078] In an embodiment of the present disclosure, in the electronic device 100, after the application processor 121 obtains a frame of fingerprint data generated by the fingerprint sensor 102, it can compare the difference between two sub-data of different phases collected based on the same configuration in the frame of fingerprint data to obtain the motion blur of the frame of fingerprint data. The sub-data contained in each frame of fingerprint data has a time sequence, and two sub-data with a longer time interval can be selected for comparison to better reflect the finger movement state. For example, the sub-data at the earliest moment and the sub-data at the last moment in each frame of fingerprint data are selected for comparison to obtain the motion blur of the frame of fingerprint data.

[0079] In one embodiment, comparing the difference between two sub-data collected at different phases based on the same configuration to obtain the motion blur of the frame fingerprint data includes: determining a difference map between the two sub-data collected at different phases based on the same configuration; determining the spatial dispersion of the difference map; and determining the motion blur of the frame fingerprint data based on the dispersion. The spatial dispersion of the difference map can be the statistical variance, statistical standard deviation, etc. of each pixel in the difference map.

[0080] The magnitude of the aforementioned discreteness is affected by factors such as finger pressure and the degree of distinction between fingerprint ridges and valleys. For example, different pressures applied by the same finger of the same user may result in different calculated discreteness. Different fingerprint ridges and valleys may also result in different calculated discreteness. Directly using discreteness as motion blur makes it difficult to establish a unified standard for fingerprint template registration based on motion blur. Specifically, a single standard cannot accommodate different pressures and degrees of distinction between fingerprint ridges and valleys. Considering that finger pressure and the degree of distinction between fingerprint ridges and valleys result in different signal amounts in fingerprint images, as a further embodiment, determining the motion blur of a frame of fingerprint data based on discreteness specifically includes: determining the signal amount of a candidate fingerprint image, and normalizing the discreteness based on the signal amount to obtain the motion blur of the frame of fingerprint data. The normalized discreteness, as the motion blur, is essentially independent of finger pressure and the degree of distinction between fingerprint ridges and valleys, facilitating the establishment of a standard for fingerprint template registration based on motion blur.

[0081] The quality of the candidate fingerprint image generated based on the fingerprint data is affected by the finger pressure, the degree of distinction between the fingerprint ridges and valleys, etc. If the fingerprint ridges and valleys are distinct and the pressure is appropriate, the quality of the candidate fingerprint image will remain high even if the finger movement is more obvious (for example, the sliding amplitude is large). When the finger movement is more obvious, the motion blur obtained in step S201 is usually higher, which may cause the candidate fingerprint image with higher quality to be discarded, thereby reducing the fingerprint template registration efficiency and increasing the fingerprint template registration time. To this end, as a further embodiment, the image quality score of the candidate fingerprint image can also be determined; the motion blur is adjusted according to the image quality score, wherein the motion blur is negatively correlated with the image quality score. The adjusted motion blur is negatively correlated with the image quality score. When registering a fingerprint template based on the motion blur, it is possible to avoid discarding the candidate fingerprint image with a higher image quality score, thereby improving the fingerprint template registration efficiency and reducing the fingerprint template registration time.

[0082] In the above embodiment, for users with good fingerprint conditions (clear fingerprint ridges and valleys), even if there is significant finger movement during the registration process (corresponding to a high pre-adjustment motion blur), candidate fingerprint images with high image quality scores can be obtained. The adjusted motion blur combines the image quality score and motion blur, preventing the discarding of candidate fingerprint images with high image quality scores. This allows users to quickly slide their finger to quickly capture a high-quality fingerprint image at a valid fingerprint location, thus quickly completing fingerprint template registration. For users with poor fingerprint conditions (unclear fingerprint ridges and valleys), a slower finger swipe can be used to register the fingerprint template.

[0083] As a further typical embodiment, the above-mentioned adjustment of motion blur based on the image quality score includes: comparing the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; and adjusting the motion blur according to the ratio corresponding to the image quality score interval. Exemplarily, a first score threshold and a second score threshold are set to divide the image quality score into three intervals. If the image quality score is greater than or equal to the first score threshold, the motion blur is reduced according to a first ratio; if the image quality score is less than the first score threshold and greater than or equal to the second score threshold, the motion blur is reduced according to a second ratio, the first ratio being greater than the second ratio; if the image quality score is less than the second score threshold, the motion blur remains unchanged. It should be understood that the embodiments of the present disclosure may set more or fewer score thresholds, and the more score thresholds there are, the more refined the adjustment of motion blur based on the image quality score.

[0084] The typical process of obtaining motion blur can be achieved by Figure 3 The flowchart shown is summarized. Figure 3A flow chart of a method for determining motion blur according to an exemplary embodiment of the present disclosure is shown. Figure 3 As shown, the method for obtaining motion blur in the embodiment of the present disclosure includes steps S301 to S309.

[0085] Step S301 : determining a difference map between two sub-data of a frame of fingerprint data collected based on the same configuration but at different phases.

[0086] For example, a frame of fingerprint data includes two phases, phase 0 and phase 1, plus a phase 2 configured with phase 0, for a total of three phases. A difference map is determined between the fingerprint image of phase 0 and the fingerprint image of phase 2 in the frame of fingerprint data.

[0087] Step S302: Determine the spatial dispersion of the difference map. Specifically, the spatial dispersion of the difference map may be a statistical variance, a statistical standard deviation, or the like of each pixel in the difference map.

[0088] Step S303: Generate a candidate fingerprint image for registration as a fingerprint template based on the frame of fingerprint data.

[0089] Step S304: Determine the signal quantity and image quality score of the candidate fingerprint image.

[0090] Step S305 , normalizing the discreteness according to the signal quantity to obtain a normalized discreteness, and obtaining an initial motion blur.

[0091] In step S306, the image quality score is compared with the first quality score threshold and the second quality score threshold. If the image quality score is greater than or equal to the first quality score threshold, the process proceeds to step S307. If the image quality score is less than the first quality score threshold and greater than or equal to the second quality score threshold, the process proceeds to step S308. If the image quality score is less than the second quality score threshold, the process proceeds to step S309.

[0092] Step S307 , reducing the initial motion blur according to a first ratio to obtain motion blur.

[0093] Step S308: Reduce the initial motion blur according to a second ratio to obtain motion blur.

[0094] The first ratio is greater than the second ratio.

[0095] In step S309, the initial motion blur is kept unchanged to obtain the motion blur. That is, if the image quality score is less than the second score threshold, the adjustment ratio is 1.

[0096] For example, the first quality score threshold is 50, and the second quality score threshold is 35. The initial motion blur is represented as S0, and the motion blur is represented as S. If the image quality score is greater than or equal to 50, the initial motion blur is reduced by a factor of 5, i.e., S = S0 / 5. If the image quality score is less than 50 and greater than or equal to 35, the initial motion blur is reduced by a factor of 2, i.e., S = S0 / 2. If the image quality score is less than 35, the initial motion blur remains unchanged, i.e., S = S0.

[0097] pass Figure 3 The motion blur is obtained using the method shown. This discreteness is normalized based on the signal intensity of the candidate fingerprint image. This normalized discreteness serves as the initial motion blur. Its magnitude is largely independent of finger pressure or the degree of distinction between fingerprint ridges and valleys, making it easier to set the standard for fingerprint template registration based on motion blur. The initial motion blur is adjusted based on the image quality score of the candidate fingerprint image. The resulting motion blur combines the image quality score and motion blur, preventing the rejection of candidate fingerprint images with high image quality scores. This increases the probability that high-quality candidate fingerprint images will pass motion blur judgment, thus reducing the fingerprint template registration time.

[0098] Step S203: registering a fingerprint template according to the motion blur of the frame of fingerprint data.

[0099] In an embodiment of the present disclosure, whether to register the candidate fingerprint image corresponding to the fingerprint data as a template can be determined based on the motion blur of the frame fingerprint data. In some implementations, it can be further determined what type of template the candidate fingerprint image is registered as.

[0100] In one embodiment, registering a fingerprint template based on the motion blur of the frame of fingerprint data specifically includes: classifying the fingerprint data based on at least one motion blur threshold to determine the motion blur type of the frame of fingerprint data; and registering the fingerprint template based on the motion blur type of the frame of fingerprint data. The motion blur type may include non-blurred and fully blurred. In some implementations, if the motion blur type is non-blurred, the corresponding candidate fingerprint image is registered as a fingerprint template; if the motion blur type is fully blurred, the corresponding fingerprint data is discarded, i.e., the candidate fingerprint image is not registered as a fingerprint template. In some implementations, the motion blur type may include non-blurred, semi-blurred, and fully blurred. If the motion blur type is non-blurred, the corresponding candidate fingerprint image is registered as a first-category fingerprint template; if the motion blur type is semi-blurred, the corresponding candidate fingerprint image is registered as a second-category fingerprint template; and if the motion blur type is fully blurred, the corresponding fingerprint data is discarded, i.e., the candidate fingerprint image is not registered as a fingerprint template. The second-category fingerprint template is used to assist the first-category fingerprint template in fingerprint matching. Specifically, the first-category fingerprint template may be a strong fingerprint template, and the second-category fingerprint template may be a weak fingerprint template. A strong fingerprint template can be used alone for fingerprint matching, while a weak fingerprint template can assist fingerprint matching but is not used alone for fingerprint matching.

[0101] As an implementation mode, the above-mentioned classification of fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the fingerprint data may specifically include: if the motion blur is less than or equal to the first motion blur threshold, determining that the motion blur type of the fingerprint data is a non-blurred type, that is, the fingerprint pattern is basically not blurred by the influence of the finger movement, and the fingerprint pattern is basically normal; if the motion blur is greater than the first motion blur threshold and less than or equal to the second motion blur threshold, determining that the motion blur type of the fingerprint data is a semi-blurred type, that is, the deformation of the fingerprint pattern affected by the finger movement is small; if the motion blur is greater than the second motion blur threshold, determining that the motion blur type of the fingerprint data is a full-blur type, that is, the fingerprint pattern is abnormal due to the influence of the finger movement.

[0102] In an embodiment of the present disclosure, before registering a candidate fingerprint image as a fingerprint template, it is further possible to determine whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image. As an embodiment, determining whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image may specifically include: detecting whether the effective area of the candidate fingerprint image is greater than an area threshold; if the effective area of the candidate fingerprint image is greater than the area threshold, detecting whether the image quality score of the candidate fingerprint image is greater than a third score threshold; if the image quality score of the candidate fingerprint image is greater than the third score threshold, registering the candidate fingerprint image as a fingerprint template. For example, when the motion blur type is a non-blur type, the corresponding candidate fingerprint image is registered as a first-category fingerprint template; when the motion blur type is a semi-blur type, the corresponding candidate fingerprint image is registered as a second-category fingerprint template.

[0103] In an embodiment of the present disclosure, it is determined whether the number of registered first-category fingerprint templates reaches a threshold; if the number of registered first-category fingerprint templates reaches the threshold, fingerprint template registration is terminated; if the number of registered first-category fingerprint templates does not reach the threshold, fingerprint data is continued to be collected through the fingerprint sensor at a first frame rate to continue fingerprint template registration.

[0104] The typical process of fingerprint template registration based on the motion blur of each frame of fingerprint data can be achieved by Figure 4 The flowchart shown is summarized. Figure 4 A flow chart of a method for registering a fingerprint template according to motion blur according to an exemplary embodiment of the present disclosure is shown. Figure 4 As shown, the method for registering a fingerprint template according to the motion blur of each frame of fingerprint data according to the embodiment of the present disclosure includes steps S401 to S407.

[0105] Step S401: Compare the motion blur of each frame of fingerprint data with a first motion blur threshold and a second motion blur threshold. The motion blur can be determined based on the embodiments of the present disclosure, for example, using Figure 3 The method shown is determined and will not be described in detail here.

[0106] If the motion blur is less than or equal to the first motion blur threshold, the motion blur type of the frame fingerprint data is determined to be a non-blur type, and the process proceeds to step S402; if the motion blur is greater than the first motion blur threshold and less than or equal to the second motion blur threshold, the motion blur type of the frame fingerprint data is determined to be a semi-blur type, and the process proceeds to step S403; if the motion blur is greater than the second motion blur threshold, the motion blur type of the frame fingerprint data is determined to be a full-blur type, and it is not registered as a fingerprint template. The fingerprint sensor continues to collect fingerprint data at the first frame rate to continue fingerprint template registration.

[0107] In step S402, a determination is made as to whether the candidate fingerprint image should be registered as a fingerprint template based on the image quality score and effective area of the candidate fingerprint image corresponding to the frame of fingerprint data. If so, the process proceeds to step S404. Otherwise, the candidate fingerprint image is not registered as a fingerprint template, and fingerprint data continues to be collected by the fingerprint sensor at the first frame rate to continue fingerprint template registration.

[0108] In step S403, a determination is made as to whether the candidate fingerprint image should be registered as a fingerprint template based on the image quality score and effective area of the candidate fingerprint image corresponding to the frame of fingerprint data. If so, the process proceeds to step S405. Otherwise, the candidate fingerprint image is not registered as a fingerprint template, and fingerprint data continues to be collected by the fingerprint sensor at the first frame rate to continue fingerprint template registration.

[0109] Step S404: register the candidate fingerprint image corresponding to the frame of fingerprint data as a strong template.

[0110] Step S405: register the candidate fingerprint image corresponding to the frame of fingerprint data as a weak template.

[0111] Step S406: Determine whether the number of registered strong templates reaches a threshold. If so, proceed to step S407. If not, continue to collect fingerprint data using the fingerprint sensor at the first frame rate to continue fingerprint template registration.

[0112] Step S407: Pack the fingerprint template to complete the registration.

[0113] The fingerprint processing method of the disclosed embodiments utilizes motions such as finger sliding during fingerprint template registration. By increasing the frame rate for fingerprint image acquisition, the registration experience is enhanced and registration time is reduced. To ensure fingerprint image quality during finger motion, the difference between two sub-data points within a frame of fingerprint data acquired using the same configuration but at different phases is compared to determine the finger motion during data acquisition. This can be used to filter out fingerprint data frames with no or insignificant motion, improving the registration experience while maintaining the template image quality and, consequently, the recognition success rate. When the fingerprint position of the finger covering the screen moves, the acquisition frame rate is increased compared to the frame rate during fingerprint recognition to improve the overall registration experience and reduce registration time. Given that finger motion speed varies significantly between users, the acquisition of distorted fingerprint signals is inevitable. The mismatch between the registered template area and the actual fingerprint pattern can significantly impact recognition efficiency. Therefore, filtering out useful signals that are substantially consistent with the actual fingerprint and selecting valid signals for data processing significantly improves recognition accuracy.

[0114] The embodiment of the present disclosure also provides a fingerprint processing device, such as Figure 5 As shown, a fingerprint processing device provided by an embodiment of the present disclosure may include: an acquisition module 501 and a registration module 502. The acquisition module 501 is used to acquire fingerprint data at a first frame rate through a fingerprint sensor during fingerprint template registration, where each frame of fingerprint data includes multiple sub-data of different phases, and at least two of the multiple sub-data of different phases are acquired based on the same configuration. The registration module 502 is used to compare the difference between two sub-data of different phases acquired based on the same configuration to obtain the motion blur of the frame of fingerprint data; and perform fingerprint template registration based on the motion blur of the frame of fingerprint data.

[0115] In some embodiments, the registration module 502 may be specifically configured to determine a difference map between two sub-data of different phases acquired based on the same configuration, determine the spatial discreteness of the difference map, and determine the motion blur of the frame fingerprint data based on the discreteness.

[0116] In some embodiments, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template based on the frame of fingerprint data. Furthermore, the registration module 502 may be configured to: determine a signal quantity of the candidate fingerprint image; and normalize the discreteness based on the signal quantity to obtain a motion blur of the frame of fingerprint data.

[0117] In some embodiments, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template based on the frame of fingerprint data. Furthermore, the registration module 502 may be configured to: determine an image quality score for the candidate fingerprint image; and adjust motion blur based on the image quality score, wherein the motion blur is negatively correlated with the image quality score.

[0118] As an implementation, the registration module 502 may be specifically configured to: compare the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; and adjust the motion blur according to a ratio corresponding to the image quality score interval.

[0119] As an implementation method, the registration module 502 can be specifically used to: classify the fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data, where the motion blur type includes a non-blurred type and a fully blurred type; and register the fingerprint template according to the motion blur type of the frame fingerprint data.

[0120] As an implementation manner, the registration module 502 can be specifically used to: if the motion blur is less than or equal to a first motion blur threshold, determine that the motion blur type of the frame fingerprint data is a non-blur type; if the motion blur is greater than the first motion blur threshold and less than or equal to a second motion blur threshold, determine that the motion blur type of the frame fingerprint data is a semi-blur type; if the motion blur is greater than the second motion blur threshold, determine that the motion blur type of the frame fingerprint data is a full-blur type.

[0121] As an embodiment, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template based on the frame of fingerprint data. Furthermore, the registration module 502 may be specifically configured to: if the fingerprint image type is semi-blurred or non-blurred, determine whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image.

[0122] Furthermore, the registration module 502 can be specifically used to: if the motion blur type of the frame fingerprint data is a non-blur type, register a first type of fingerprint template according to the frame fingerprint data; if the motion blur type of the fingerprint data is a semi-blur type, register a second type of fingerprint template according to the frame fingerprint data.

[0123] In some embodiments, the fingerprint processing device can be used with Figure 1A 、 Figure 1B and Figure 1C The fingerprint sensor 102 shown forms a fingerprint recognition system inside the electronic device 100, wherein the fingerprint processing device can be specifically Figure 1B and 1C The fingerprint processing device shown can be configured in the application processor 121 (e.g., central processing unit (CPU)) of the electronic device 100 to execute the main steps of the fingerprint processing methods described in the above embodiments. In other alternative embodiments, the fingerprint processing device can also be implemented using other processing units or control units with image processing capabilities (e.g., microcontrollers (MCUs)).

[0124] In some embodiments, the fingerprint processing device may be composed of Figure 6 The modules shown are implemented as follows. Figure 6As shown, the modules of the fingerprint system 600 include: an ultrasonic fingerprint sensor 601, a controller 602, a data processor 603, an analog-to-digital converter 604, and an algorithm processor 605. Among them, each module is controlled by the controller 602, which controls the ultrasonic fingerprint sensor 601 to generate and receive signals, completes the digital-to-analog conversion through the ultrasonic fingerprint sensor 601, and completes the rearrangement and packaging of the data through the data processor 603. The converted data is sent to the algorithm processor 605 for algorithm processing to complete the fingerprint template registration and recognition. The algorithm processor 605 can execute the main steps of the fingerprint processing method described in the above embodiments. The controller 602, the data processor 603, the analog-to-digital converter 604, and the algorithm processor 605 can serve as Figure 1C The control system 120 is shown as an implementation mode. The functions of the fingerprint processing device are divided into the controller 602, the data processor 603, the analog-to-digital converter 604 and the algorithm processor 605.

[0125] Sliding fingerprint template registration is implemented in an ultrasonic fingerprint system. Benefiting from the high acquisition frame rate of ultrasonic signals processed by the ultrasonic fingerprint sensor 601, during the ultrasonic fingerprint template registration process, unlike traditional finger press registration methods, registration can be performed using motion methods such as finger sliding. By increasing the ultrasonic signal frame rate to collect fingerprint signals, the registration experience is improved and registration time is reduced. To ensure fingerprint image quality during motion, the difference between fingerprint images at different time points during the finger motion is compared to determine the finger motion state during data collection. This can be used to filter out image signals without obvious motion, improving the registration experience while not affecting the template image quality and thus the recognition success rate. Compared with other solutions that use press-and-lift template registration, the higher ultrasonic signal frame rate allows more data to be collected in a shorter time even during motion. This makes it easier to obtain images without motion blur, effectively completing signal acquisition of the finger's fingerprint position in a shorter time, improving the fingerprint template registration experience and efficiency.

[0126] The embodiments of the present disclosure further provide an electronic device 100, comprising a device body 101 and the aforementioned fingerprint sensor 102 disposed on the device body 101. In some embodiments, the electronic device 100 may be a portable electronic device, such as a smartphone, tablet computer, laptop computer, personal digital assistant, etc. Alternatively, the electronic device 100 may be a smart wearable device, which is not limited in the embodiments of the present disclosure.

[0127] The electronic device 100 provided by the embodiment of the present disclosure may further include: an application processor 121; and a memory storing a program, wherein the program includes instructions, and when the instructions are executed by the application processor 121, the application processor 121 executes the method of the above embodiment, for example Figures 2 to 4 The method shown.

[0128] The embodiments of the present disclosure further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable the application processor 121 of the electronic device 100 to execute the method of the above embodiment, for example Figures 2 to 4 The method shown.

[0129] refer to Figure 7 , which is a structural block diagram of an electronic device 700 provided in an embodiment of the present disclosure, and is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device 700 may include: a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. Various programs and data required for the operation of the electronic device 700 can also be stored in the RAM 703. The computing unit 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0130] Multiple components within electronic device 700 are connected to I / O interface 705, including an input unit 706, an output unit 707, a storage unit 708, and a communication unit 709. Input unit 706 can be any type of device capable of inputting information into electronic device 700. Input unit 706 can receive input numeric or character information and generate key signal inputs related to user settings and / or function control of the electronic device. Output unit 707 can be any type of device capable of presenting information and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. Storage unit 708 may include, but is not limited to, a magnetic disk or an optical disk. Communication unit 709 allows electronic device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and / or a chipset, such as a Bluetooth device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0131] The computing unit 701 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described in this disclosure. For example, in some embodiments, the fingerprint processing methods of the embodiments of the present disclosure can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 700 via the ROM 702 and / or the communication unit 709. In some embodiments, the computing unit 701 can be configured to perform the methods of this embodiment through any other suitable means (e.g., via firmware).

[0132] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0133] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0134] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., a magnetic disk, an optical disk, a memory, a programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0135] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0136] The above are merely preferred embodiments of the present disclosure and are not intended to limit the present disclosure in any form. Although the present disclosure has been disclosed as above with preferred embodiments, they are not intended to limit the present disclosure. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present disclosure. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present disclosure without departing from the content of the technical solution of the present disclosure are still within the scope of the technical solution of the present disclosure.

Claims

1. A fingerprint processing method, characterized in that: include: During the fingerprint template registration process, fingerprint data is collected by the ultrasonic fingerprint sensor at a first frame rate, each frame of fingerprint data includes a plurality of sub-data at different phases, and at least two of the plurality of sub-data at different phases are collected based on the same configuration; Comparing the difference between two sub-data collected at different phases based on the same configuration to obtain the motion blur of the frame fingerprint data, wherein the motion blur represents the possibility and degree of mismatch between the collected fingerprint pattern and the actual fingerprint pattern caused by finger movement; Registering a fingerprint template according to the motion blur of the frame fingerprint data includes: fusing a plurality of sub-data of different phases of the frame fingerprint data to obtain a candidate fingerprint image corresponding to the frame fingerprint data; The candidate fingerprint image is registered as a fingerprint template according to the motion blur of the frame fingerprint data.

2. The method according to claim 1, wherein The comparing the difference between two sub-data collected based on the same configuration and at different phases to obtain the motion blur of the frame fingerprint data includes: determining a difference map between the two sub-data of different phases acquired based on the same configuration; Determining the dispersion of the difference map in the spatial domain; The motion blur of the frame fingerprint data is determined according to the discreteness.

3. The method according to claim 2, wherein The determining the motion blur of the frame fingerprint data according to the discreteness includes: determining a signal amount of the candidate fingerprint image; The discreteness is normalized according to the signal quantity to obtain the motion blur of the frame fingerprint data.

4. The method according to claim 2, wherein The comparing the difference between two sub-data with different phases collected based on the same configuration to obtain the motion blur of the frame fingerprint data also includes: determining an image quality score of the candidate fingerprint image; The motion blur is adjusted according to the image quality score, wherein the motion blur is negatively correlated with the image quality score.

5. The method according to claim 4, wherein Adjusting the motion blur according to the image quality score comprises: comparing the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; The motion blur is adjusted according to a ratio corresponding to the image quality score interval.

6. The method according to claim 5, wherein If the image quality score is greater than or equal to a first score threshold, reducing the motion blur according to a first ratio; If the image quality score is less than the first score threshold and greater than or equal to a second score threshold, reducing the motion blur according to a second ratio, the first ratio being greater than the second ratio; If the image quality score is less than the second score threshold, the motion blur is kept unchanged.

7. The method according to claim 1, wherein The registering of a fingerprint template according to the motion blur of the frame fingerprint data includes: classifying the frame fingerprint data according to at least one motion blur threshold to obtain a motion blur type of the frame fingerprint data, wherein the motion blur type includes a non-blurred type and a fully blurred type; Fingerprint template registration is performed according to the motion blur type of the frame fingerprint data.

8. The method according to claim 7, wherein The classifying the frame fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data includes: If the motion blur is less than or equal to a first motion blur threshold, determining that the motion blur type of the frame fingerprint data is a non-blur type; If the motion blur is greater than the first motion blur threshold and less than or equal to the second motion blur threshold, determining that the motion blur type of the frame fingerprint data is a semi-blur type; If the motion blur is greater than the second motion blur threshold, it is determined that the motion blur type of the frame fingerprint data is a full blur type.

9. The method according to claim 8, wherein The registering of a fingerprint template according to the motion blur type of the frame fingerprint data includes: If the type of the fingerprint image is a semi-blur type or a non-blur type, whether to register the candidate fingerprint image as a fingerprint template is determined according to the image quality score and / or the effective area of the candidate fingerprint image.

10. The method according to claim 9, wherein The determining whether to register the candidate fingerprint image as a fingerprint template according to the image quality score and / or the effective area of the candidate fingerprint image includes: Detecting whether the effective area of the candidate fingerprint image is greater than an area threshold; If the effective area of the candidate fingerprint image is greater than the area threshold, detecting whether the image quality score of the candidate fingerprint image is greater than a third score threshold; If the image quality score of the candidate fingerprint image is greater than the third score threshold, the candidate fingerprint image is registered as a fingerprint template.

11. The method according to any one of claims 7 to 10, characterized in that The registering of a fingerprint template according to the motion blur type of the frame fingerprint data includes: If the motion blur type of the frame fingerprint data is a non-blur type, performing a first type fingerprint template registration according to the frame fingerprint data; If the motion blur type of the frame fingerprint data is a semi-blur type, a second type of fingerprint template registration is performed according to the frame fingerprint data.

12. The method according to claim 11, wherein The second type of fingerprint template is used to assist the first type of fingerprint template in fingerprint matching.

13. The method according to claim 11, wherein Also includes: Determine whether the number of registered first-category fingerprint templates reaches a threshold; If the number of registered fingerprint templates of the first category reaches the threshold, the fingerprint template registration is terminated; If the number of registered first-category fingerprint templates does not reach the threshold, continue the step of collecting fingerprint data using the ultrasonic fingerprint sensor at the first frame rate.

14. The method according to claim 1, wherein Also includes: During the fingerprint recognition process, fingerprint data is collected by the ultrasonic fingerprint sensor at a second frame rate, wherein the first frame rate is greater than the second frame rate.

15. The method according to claim 1, wherein The fingerprint template registration process includes a process in which a finger is in continuous contact with a fingerprint collection area and moves, wherein the movement is used to change the fingerprint position where the finger is in contact with the fingerprint collection area.

16. A fingerprint processing device, characterized in that: include: an acquisition module, configured to acquire fingerprint data at a first frame rate using an ultrasonic fingerprint sensor during fingerprint template registration, wherein each frame of fingerprint data includes a plurality of sub-data at different phases, and at least two of the plurality of sub-data at different phases are acquired based on the same configuration; A registration module is configured to compare the difference between two sub-data collected at different phases based on the same configuration to obtain the motion ambiguity of the frame fingerprint data, wherein the motion ambiguity indicates the possibility and degree of mismatch between the collected fingerprint pattern and the actual fingerprint pattern caused by finger movement; Registering a fingerprint template according to the motion blur of the frame fingerprint data includes: fusing a plurality of sub-data of different phases of the frame fingerprint data to obtain a candidate fingerprint image corresponding to the frame fingerprint data; The candidate fingerprint image is registered as a fingerprint template according to the motion blur of the frame fingerprint data.

17. The device according to claim 16, wherein The registration module is used to determine a difference map of two sub-data with different phases collected based on the same configuration, determine the discreteness of the difference map in the spatial domain, and determine the motion blur of the frame fingerprint data according to the discreteness.

18. The device according to claim 17, wherein The registration module is used to determine the signal amount of the candidate fingerprint image; and normalize the discreteness according to the signal amount to obtain the motion blur of the frame fingerprint data.

19. The device according to claim 17, wherein The registration module is configured to determine an image quality score of the candidate fingerprint image; and adjust the motion blur according to the image quality score, wherein the motion blur is negatively correlated with the image quality score.

20. The device according to claim 19, wherein The registration module is configured to compare the image quality score with at least one quality score threshold to obtain an image quality score interval corresponding to the image quality score; and adjust the motion blur according to a ratio corresponding to the image quality score interval.

21. The device according to claim 16, wherein The registration module is used to classify the frame fingerprint data according to at least one motion blur threshold to obtain the motion blur type of the frame fingerprint data, where the motion blur type includes a non-blur type and a full-blur type; and register the fingerprint template according to the motion blur type of the frame fingerprint data.

22. The device according to claim 20, wherein The registration module is configured to determine that the motion blur type of the frame fingerprint data is a non-blur type if the motion blur is less than or equal to a first motion blur threshold; determine that the motion blur type of the frame fingerprint data is a semi-blur type if the motion blur is greater than the first motion blur threshold and less than or equal to a second motion blur threshold; and determine that the motion blur type of the frame fingerprint data is a full-blur type if the motion blur is greater than the second motion blur threshold.

23. The device according to claim 21, wherein The registration module is configured to determine whether to register the candidate fingerprint image as a fingerprint template based on the image quality score and / or effective area of the candidate fingerprint image if the type of the fingerprint image is a semi-blurred type or a non-blurred type.

24. The device according to claim 21, wherein The registration module is configured to register a first type of fingerprint template based on the frame fingerprint data if the motion blur type of the frame fingerprint data is a non-blur type; and to register a second type of fingerprint template based on the frame fingerprint data if the motion blur type of the frame fingerprint data is a semi-blur type.

25. An electronic device, characterized in that: include: Ultrasonic fingerprint sensor; A fingerprint processing device according to any one of claims 16 to 24.

26. An electronic device comprising: processor; as well as A memory storing a program, wherein the program comprises instructions which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 15.

27. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 15.

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