Fingerprint processing method and apparatus, and electronic device

Abstract

Provided in the embodiments of the present disclosure are a fingerprint processing method and apparatus, and an electronic device. The fingerprint processing method comprises: during a fingerprint template registration process, collecting fingerprint data at a first frame rate by means of a fingerprint sensor, wherein each frame of fingerprint data comprises a plurality of pieces of sub-data of different phases, and at least two pieces of the plurality of pieces of sub-data of different phases are collected on the basis of the same configuration; comparing two pieces of the sub-data of different phases that are collected on the basis of the same configuration to obtain a difference, so as to obtain a motion blur degree of the frame of fingerprint data; and on the basis of the motion blur degree of the frame of fingerprint data, performing fingerprint template registration. By means of the use of the embodiments of the present disclosure, a finger can remain in continuous contact with and move within a fingerprint collection area during a fingerprint template registration process, without being limited to a repeated pressing-and-lifting manner, which can improve the flexibility of user input during the fingerprint template registration, improve the efficiency of the fingerprint template registration, and ensure the quality of a registered fingerprint template.

Description

Fingerprint processing method and device and electronic device

[0001] The present disclosure claims priority to the Chinese patent application No. 2024113763245, filed on September 30, 2024, and entitled "Fingerprint processing method and device and electronic device", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present disclosure relates to the field of fingerprint identification, and in particular, to a fingerprint processing method, device and electronic device. BACKGROUND

[0003] An ultrasonic fingerprint identification system acquires corresponding fingerprint images by emitting and receiving ultrasonic signals, and uses the difference in acoustic impedance between the screen, the finger and the air to distinguish the valleys and ridges on the fingerprint, so as to obtain fingerprint features for identification. In the application process, the fingerprint lines of the finger need to be collected first as a template for identification, so the fingerprint template has an important influence on identification.

[0004] In related technologies, the fingerprint position of the finger is collected by repeatedly pressing and lifting the hand for template registration. During the fingerprint template registration process, the user is required to repeatedly place the finger on the fingerprint sensor, and after each placement, the user is required to lift the finger and adjust the position of the finger so that other positions of the finger are in contact with the fingerprint sensor when the finger is placed on the fingerprint sensor again. This repeated pressing and lifting method is low in efficiency, resulting in a long fingerprint template registration process. In addition, if the finger moves during the pressing process, the fingerprint image is distorted due to the influence of the movement, etc., so that the registered fingerprint template is greatly different from the actual fingerprint, affecting the final fingerprint identification performance. SUMMARY

[0005] 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.

[0006] In a first aspect, the embodiments of the present disclosure provide a fingerprint processing method, comprising: in a fingerprint template registration process, acquiring fingerprint data by a fingerprint sensor according to a first frame rate, each frame of fingerprint data comprising a plurality of different phase sub-data, at least two of the plurality of different phase sub-data being acquired based on the same configuration; comparing the difference between two different phase sub-data acquired based on the same configuration to obtain the motion blur degree of the frame of fingerprint data; and performing fingerprint template registration according to the motion blur degree of the frame of fingerprint data.

[0007] Optionally, the motion blur degree of the frame fingerprint data is obtained by comparing the difference between the two sub-data of different phases acquired based on the same configuration, comprising: 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; and determining the motion blur degree of the frame fingerprint data according to the dispersion.

[0008] Optionally, the method further comprises: determining a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data; and the determining the motion blur degree of the frame fingerprint data according to the dispersion comprises: determining the signal quantity of the candidate fingerprint image; and normalizing the dispersion according to the signal quantity to obtain the motion blur degree of the frame fingerprint data.

[0009] Optionally, the method further comprises: determining a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data; and the comparing the difference between the two sub-data of different phases acquired based on the same configuration to obtain the motion blur degree of the frame fingerprint data further comprises: determining an image quality score of the candidate fingerprint image; and adjusting the motion blur degree according to the image quality score, wherein the motion blur degree is negatively correlated with the image quality score.

[0010] Optionally, the adjusting the motion blur degree 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; and adjusting the motion blur degree according to a proportion corresponding to the image quality score interval.

[0011] Optionally, if the image quality score is greater than or equal to a first score threshold, the motion blur degree is reduced by a first proportion; 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 degree is reduced by a second proportion, the first proportion being greater than the second proportion; and if the image quality score is less than the second score threshold, the motion blur degree is kept unchanged.

[0012] Optionally, the fingerprint template registration according to the motion blur degree of the frame fingerprint data comprises: classifying the frame fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame fingerprint data, the motion blur type comprising a non-blur type and a full-blur type; and performing the fingerprint template registration according to the motion blur type of the frame fingerprint data.

[0013] Optionally, the classifying the frame fingerprint data according to the at least one motion blur degree threshold to obtain a motion blur type of the frame fingerprint data comprises: if the motion blur degree is less than or equal to a first motion blur degree threshold, determining that the motion blur type of the frame fingerprint data is a non-blur type; if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to a second motion blur degree threshold, determining that the motion blur type of the frame fingerprint data is a semi-blur type; and if the motion blur degree is greater than the second motion blur degree threshold, determining that the motion blur type of the frame fingerprint data is a full-blur type.

[0014] Optionally, the method further comprises: determining a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data; and the registering the fingerprint template according to the motion blur type of the frame fingerprint data comprises: if the type of the fingerprint image is the semi-blur type or the non-blur type, determining whether to register the candidate fingerprint image as the fingerprint template according to an image quality score and / or an effective area of the candidate fingerprint image.

[0015] Optionally, the determining whether to register the candidate fingerprint image as the fingerprint template according to the image quality score and / or the effective area of the candidate fingerprint image comprises: 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 an image quality score of the candidate fingerprint image is greater than a third score threshold; and if the image quality score of the candidate fingerprint image is greater than the third score threshold, registering the candidate fingerprint image as the fingerprint template.

[0016] Optionally, the registering the fingerprint template according to the motion blur type of the frame fingerprint data comprises: if the motion blur type of the frame fingerprint data is the non-blur type, performing a first type of fingerprint template registration according to the frame fingerprint data; and if the motion blur type of the frame fingerprint data is the semi-blur type, performing a second type of fingerprint template registration according to the frame fingerprint data.

[0017] Optionally, the second type of fingerprint template is used to assist the first type of fingerprint template in fingerprint matching.

[0018] Optionally, the method further comprises: determining whether the registered first type of fingerprint template reaches a quantity threshold; if the registered first type of fingerprint template reaches the quantity threshold, ending the fingerprint template registration; and if the registered first type of fingerprint template does not reach the quantity threshold, continuing the step of collecting the fingerprint data by the fingerprint sensor at the first frame rate.

[0019] Optionally, the method further comprises: in a fingerprint identification process, collecting fingerprint data by the fingerprint sensor at a second frame rate, wherein the first frame rate is greater than the second frame rate.

[0020] Optionally, the fingerprint template registration process comprises a process in which the finger continuously contacts the fingerprint collection area and moves to change the fingerprint position contacting the fingerprint collection area.

[0021] Optionally, the fingerprint sensor comprises an ultrasonic fingerprint sensor.

[0022] In a second aspect, the embodiments of the present disclosure further provide a fingerprint processing apparatus, comprising: a collection module configured to collect, in a fingerprint template registration process, fingerprint data by a fingerprint sensor at a first frame rate, each frame of the fingerprint data comprising a plurality of sub-data of different phases, at least two of the plurality of sub-data of different phases being collected based on a same configuration; a registration module configured to compare a difference between the two sub-data of different phases collected based on the same configuration to obtain a motion blur degree of the frame of the fingerprint data; and perform fingerprint template registration according to the motion blur degree of the frame of the fingerprint data.

[0023] Optionally, the registration module is configured to determine a difference map of the two sub-data of different phases collected based on the same configuration, determine a dispersion degree of the difference map in a spatial domain, and determine the motion blur degree of the frame of the fingerprint data according to the dispersion degree.

[0024] Optionally, the registration module is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame of the fingerprint data, and determine a signal quantity of the candidate fingerprint image; and the registration module is configured to normalize the dispersion degree according to the signal quantity to obtain the motion blur degree of the frame of the fingerprint data.

[0025] Optionally, the registration module is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame of the fingerprint data, and determine an image quality score of the candidate fingerprint image; and the registration module is configured to adjust the motion blur degree according to the image quality score, wherein the motion blur degree is negatively correlated with the image quality score.

[0026] 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 degree according to a proportion corresponding to the image quality score interval.

[0027] Optionally, the registration module is configured to classify the frame of the fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame of the fingerprint data, the motion blur type comprising a non-blur type and a full-blur type, and perform fingerprint template registration according to the motion blur type of the frame of the fingerprint data.

[0028] Optionally, the registration module is configured to determine, if the motion blur degree is less than or equal to a first motion blur degree threshold, that the motion blur type of the frame fingerprint data is a non-blurred type; determine, if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to a second motion blur degree threshold, that the motion blur type of the frame fingerprint data is a semi-blurred type; and determine, if the motion blur degree is greater than the second motion blur degree threshold, that the motion blur type of the frame fingerprint data is a fully-blurred type.

[0029] Optionally, the registration module is further configured to determine, according to the frame fingerprint data, a candidate fingerprint image for registration as a fingerprint template; and the registration module is configured to determine, if the type of the fingerprint image is the semi-blurred type or the non-blurred type, whether to register the candidate fingerprint image as the fingerprint template according to an image quality score and / or an effective area of the candidate fingerprint image.

[0030] Optionally, the registration module is configured to perform a first type of fingerprint template registration according to the frame fingerprint data, if the motion blur type of the frame fingerprint data is the non-blurred type; and perform a second type of fingerprint template registration according to the frame fingerprint data, if the motion blur type of the frame fingerprint data is the semi-blurred type.

[0031] In a third aspect, the embodiments of the present disclosure further provide an electronic device, comprising: a fingerprint sensor; and the fingerprint processing apparatus described above.

[0032] In a fourth aspect, the embodiments of the present disclosure further provide an electronic device, comprising: a processor; and a memory storing programs, wherein the programs include instructions that, when executed by the processor, cause the processor to perform the method described above.

[0033] In a fifth aspect, 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 cause a computer to perform the method described above.

[0034] The fingerprint processing method, apparatus and electronic device provided by the embodiments of the present disclosure can at least partially avoid registering a fingerprint image that is distorted due to finger movement as a fingerprint template, so that the finger can be in continuous contact with the fingerprint capturing area and move during the fingerprint template registration process, rather than being limited to repeated pressing-lifting, thereby improving the flexibility of user input during the fingerprint template registration, improving the efficiency of the fingerprint template registration and ensuring the quality of the registered fingerprint template.

[0035] These and other aspects of the present disclosure will become more apparent from the following description of embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0037] FIG. 1A shows a schematic diagram of an electronic device to which an embodiment of the present disclosure can be applied.

[0038] FIG. 1B shows a schematic diagram of another electronic device to which an embodiment of the present disclosure can be applied.

[0039] FIG. 1C shows a system block diagram of an electronic device to which an embodiment of the present disclosure can be applied.

[0040] FIG. 2 shows a flowchart of a fingerprint processing method according to an embodiment of the present disclosure.

[0041] FIG. 3 shows a flowchart of a motion blur degree determination method according to an embodiment of the present disclosure.

[0042] FIG. 4 shows a flowchart of a method of registering a fingerprint template according to a motion blur degree according to an embodiment of the present disclosure.

[0043] FIG. 5 shows a structural block diagram of a fingerprint processing apparatus according to an embodiment of the present disclosure.

[0044] FIG. 6 shows a structural block diagram of an ultrasonic fingerprint processing system according to an embodiment of the present disclosure.

[0045] FIG. 7 shows a structural block diagram of an exemplary electronic device that can be used to implement an embodiment of the present disclosure. DETAILED DESCRIPTION

[0046] Embodiments of the present disclosure are described in detail below with reference to the attached drawings, which show by way of illustration the embodiments in which the same or similar elements are denoted by the same or similar reference numerals throughout the various figures. The embodiments described below are exemplary only, and are not to be understood as limiting the present disclosure.

[0047] In order to make the personnel in the technical field better understand the scheme of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, not all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by the person skilled in the art without creative labor are within the scope of protection of the present disclosure.

[0048] It should be noted that in the embodiments of the present disclosure, in this paper, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations.

[0049] Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the sentence "including a…" does not exclude the presence of other identical elements in the process, method, article or equipment including the element.

[0050] In the description of the embodiments of the present disclosure, the words "example" or "for example" are used to represent example, illustration or description. Any embodiment or design scheme described as "example" or "for example" in the embodiments of the present disclosure is not interpreted as more preferred or having more advantages than another embodiment or design scheme. The use of the words "example" or "for example" and the like is intended to present the relative concept in a clear manner.

[0051] In addition, "multiple" in the embodiments of the present disclosure means two or more than two, and therefore "multiple" in the embodiments of the present disclosure can also be understood as "at least two". "At least one" can be understood as one or more, for example, as 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, which can include A, B, C, A and B, A and C, B and C, or A and B and C.

[0052] It should be noted that in the embodiments of the present disclosure, the "and / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases of A alone, A and B together, and B alone. In addition, the character " / ", if not specially specified, generally represents a "or" relationship between the front and rear associated objects.

[0053] FIGS. 1A and 1B show schematic diagrams of an electronic device in which various schemes described herein can be implemented, as shown in FIGS. 1A and 1B, the electronic device 100 can include a device body 101 and a fingerprint sensor 102. The fingerprint sensor 102 can capture a fingerprint image for fingerprint recognition. The fingerprint sensor 102 can 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 can be set on the side, back, front or under the display of the front of the device body 101 according to the actual product design needs.

[0054] In some embodiments, the electronic device 100 can be a portable electronic device, which can be a smartphone, a tablet computer, a notebook computer, a personal digital assistant, etc. In other embodiments, the electronic device 100 can also be a smart wearable device, and the type of the electronic device 100 is not limited in the embodiments of the present disclosure.

[0055] In some embodiments, the fingerprint sensor 102 can be specifically arranged on the side of the device body 101 of the electronic device 100; as smartphones or other portable electronic devices develop towards thinness or foldability, the thickness of the electronic device 100 becomes smaller and smaller, resulting in the fingerprint sensor 102 arranged on the side of the device body 101 becoming narrower and narrower.

[0056] Referring to FIG. 1A, as a typical embodiment, the device body 101 includes a display 10 and a middle frame 20. The display 10 is located on the front of the device body 101, used for displaying pictures and providing a human-machine interface for users; the middle frame 20 is generally located between the display 10 and the back shell of the electronic device, used to support the display 10 and carry various functional components inside the device body 101, such as a mainboard, a battery, a camera, a speaker, a microphone, various sensor units, etc. In specific embodiments, the middle frame 20 includes a bezel located at the periphery of the device body 101, which can include multiple sides and carry power keys, volume keys or other function keys, wherein the fingerprint sensor 102 can be arranged on one side of the bezel and has a sensing area 108. In specific embodiments, the fingerprint sensor 102 can be specifically a fingerprint recognition chip or a fingerprint module with a fingerprint recognition chip, which can be integrated above the power key or the volume key on the side of the bezel, embedded in a predetermined area on the side of the bezel, or attached to the inner surface of the side of the bezel, for users to input fingerprints to realize the side fingerprint function of the electronic device 100.

[0057] In some embodiments, the fingerprint sensor 102 can be specifically arranged under the display screen of the electronic device 100, which is located on the front of the device body 101, for displaying pictures and providing a human-computer interaction interface for the user. Compared with the case where the fingerprint sensor 102 is arranged on the front of the device body outside the display screen, the arrangement of the fingerprint sensor 102 under the display screen of the electronic device 100 can improve the screen-to-body ratio of the electronic device. The fingerprint sensor 102 can penetrate various materials by using ultrasonic or optical penetration technology, and can emit ultrasonic signals or optical signals to the outer surface of the display screen, and receive the reflected signals reflected by the finger, so as to realize fingerprint image acquisition and fingerprint recognition.

[0058] Referring to FIG. 1B, as another typical embodiment, the difference between the embodiment of FIG. 1A is that the fingerprint sensor 102 is arranged under the display screen 10, i.e., inside the display screen 10. The display screen 10 includes, from top to bottom, a cover glass 11, a touch panel 12, and a display panel 13. The fingerprint sensor 102 can be arranged under the display panel 13. The fingerprint sensor 102 has a sensing area 108, and the area on the display screen 10 corresponding to the sensing area 108 is a fingerprint acquisition area. A visual prompt can be displayed on the fingerprint acquisition area on the screen 10 to inform the user of the location of the fingerprint acquisition area. The fingerprint sensor 102 can emit signals by using ultrasonic or optical penetration technology, so that the signals can penetrate the cover glass 11, the touch panel 12, and the display panel 13. The signals can be reflected by the finger located on the outer surface of the cover glass 11 to form reflected signals, and the reflected signals can penetrate the cover glass 11, the touch panel 12, and the display panel 13 to reach the sensing area 108 of the fingerprint sensor 102. The fingerprint sensor 102 can generate a fingerprint image based on the reflected signals.

[0059] Referring to FIG. 1C, the fingerprint sensor 102 includes a sensing array 103, an output module 104, an interface module 105, and a driving module 106. The sensing array 103 is configured to couple with the user's finger to acquire the fingerprint information of the user's finger when the user presses the fingerprint sensor 102 to input the fingerprint. The sensing array 103 specifically includes a plurality of sensing electrodes arranged in an array. The area where the sensing array 103 is located or the effective fingerprint acquisition area thereof is the sensing area 108 of the fingerprint sensor 102. The driving module 106 and the output module 104 are connected with the sensing array 103 and the interface module 105, respectively. The driving module 106 is configured to drive the sensing array 103 to perform fingerprint scanning to acquire the fingerprint information of the user's finger. The output module 104 is configured to generate corresponding fingerprint data based on the fingerprint information acquired by the sensing array 103, and output the fingerprint data to the control system 120 through the interface module 105. The interface module 105 can be specifically a serial peripheral interface (SPI).

[0060] With continued reference to FIG. 1C, the control system 120 can include one or more general purpose single- or multi-chip processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, or combinations thereof. According to some examples, the control system 120 can include a special purpose component for controlling the fingerprint sensor 102. In some implementations, the functionality of the control system 120 can be divided among one or more controllers or processors, such as between a special purpose sensor controller and an application processor of the electronic device. With reference to FIG. 1C, the control system 120 can include an application processor 121 of the electronic device. The application processor 121 can be embodied as a central processing unit (CPU) or other processing unit or control unit having processing capabilities, such as a microcontroller (MCU), within the electronic device 100 that is connected to the interface module 105 and includes fingerprint processing apparatus, primarily for controlling the operating state of the fingerprint sensor 102 and processing fingerprint data output by the fingerprint sensor 102 and performing fingerprint template enrollment and fingerprint matching verification to determine whether a currently captured fingerprint image belongs to a legitimate fingerprint and to unlock the electronic device 100 or perform other functions related to fingerprint recognition based on the determination.

[0061] Fingerprint recognition generally includes a fingerprint template enrollment phase and a fingerprint verification phase. In the fingerprint template enrollment phase, a user input fingerprint is captured to form a fingerprint template. In the fingerprint verification phase, a user input fingerprint is captured to obtain a query fingerprint image, and the query fingerprint image is matched with the enrolled fingerprint template to verify whether the query fingerprint image belongs to a legitimate fingerprint. To reduce the false rejection rate, in the fingerprint template enrollment phase, multiple templates corresponding to an image of a finger are obtained. Referring to FIG. 1A, the narrow fingerprint sensor 102 results in a small fingerprint position that can be captured, i.e., one fingerprint image is for a small fingerprint position on a finger, and the fingerprint position of the user acting on the fingerprint sensor 102 is variable, so multiple fingerprint images need to be captured for fingerprint template enrollment to obtain multiple templates, so as to reduce the false rejection rate of fingerprint recognition. Referring to FIG. 1B, the under-screen fingerprint sensor 102 can have a large sensing area, and due to user pressing habits and the like, the fingerprint position of the user acting on the fingerprint sensor 102 is also relatively variable, so multiple fingerprint images need to be captured for fingerprint template enrollment to obtain multiple templates, so as to reduce the false rejection rate of fingerprint recognition.

[0062] In order to obtain multiple templates, in a fingerprint template registration process, a user is required to repeatedly place a finger on a fingerprint sensor, after each placement, the user is required to lift the finger and adjust the position of the finger so that other positions of the finger are in contact with the fingerprint sensor when the finger is placed on the fingerprint sensor again, thereby registering multiple fingerprint templates of multiple positions of the finger. This repeated pressing and lifting method is inefficient, resulting in a long fingerprint template registration process. In addition, if the finger moves during pressing, the affected fingerprint image is distorted, etc., so that the registered fingerprint template is significantly different from the actual fingerprint, affecting the final fingerprint recognition performance.

[0063] The fingerprint processing method provided in the embodiments of the present disclosure can be applied to the electronic device 100 shown in FIG. 1A and FIG. 1B to improve the fingerprint template registration experience.

[0064] FIG. 2 shows a flowchart of a fingerprint processing method according to an exemplary embodiment of the present disclosure. As shown in FIG. 2, the fingerprint processing method of the embodiments of the present disclosure can be applied to the fingerprint template registration stage, which can at least partially avoid registering a distorted fingerprint image affected by finger movement as a fingerprint template, so that the finger can be in continuous contact with the fingerprint collection area and move during the fingerprint template registration process, without being limited to the repeated pressing and lifting method. This can improve user input flexibility in fingerprint template registration, improve fingerprint template registration efficiency and ensure the quality of the registered fingerprint template. The specific steps include the following.

[0065] In step S201, during the fingerprint template registration process, the fingerprint sensor collects fingerprint data at a first frame rate, and each frame of fingerprint data includes multiple sub-data of different phases, at least two of which are collected based on the same configuration.

[0066] In the embodiments of the present disclosure, in the electronic device 100, the fingerprint sensor 102 can detect the contact of the user's finger or start the fingerprint collection function 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.

[0067] For example, when the fingerprint sensor 102 is a capacitive fingerprint sensor, the plurality of sensing electrodes of the sensing array 103 can form different coupling capacitances with the ridges and valleys of a user's finger. The fingerprint sensor 102 can detect the capacitance signals formed by the ridges and valleys of the user's finger and the sensing electrodes of the sensing array 103, and thus can acquire the fingerprint information of the portion of the user's finger that is pressed against the sensing region 108. The fingerprint sensor 102 can generate a fingerprint image based on the acquired fingerprint information. The fingerprint image can be a digital image that is formed by integrating the fingerprint information of the corresponding positions of the user's finger acquired by all of the sensing electrodes of the sensing array 103. The fingerprint sensor 102 can perform some processing on the generated fingerprint image, and temporarily store the fingerprint image in the fingerprint sensor 102, to wait for the application processor 121 of the electronic device 100 to acquire the fingerprint image.

[0068] For example, when the fingerprint sensor 102 is an ultrasonic fingerprint sensor, the ultrasonic transmitter of the fingerprint sensor 102 can emit ultrasonic signals, which can pass through the skin surface and be reflected by the ridges and valleys of the fingerprint. The ridges can reflect more ultrasonic energy than the valleys. The ultrasonic receiver of the fingerprint sensor 102 can receive the reflected signals and convert them into electrical signals that indicate the reflected ultrasonic energy. The fingerprint sensor 102 can acquire the fingerprint information of the portion of the user's finger that is pressed against the sensing region 108, and generate a fingerprint image based on the acquired fingerprint information. In some implementations, the ultrasonic transmitter of the fingerprint sensor 102 can include a piezoelectric transmitter layer that can generate ultrasonic waves by expanding or contracting in response to an applied signal. Referring to FIG. IB, the ultrasonic waves generated by the piezoelectric transmitter layer can pass through the display panel 13, the touch panel 12, and the cover glass 11, and be reflected by the ridges and valleys of the fingerprint. The ultrasonic receiver of the fingerprint sensor 102 can include a piezoelectric receiver layer and an array of pixel circuits. Each pixel circuit can be configured to convert electrical charges generated in the piezoelectric receiver layer proximate to the pixel circuit into electrical signals. Each pixel circuit can include a pixel input electrode that couples the piezoelectric receiver layer to the pixel circuit.

[0069] 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 a plurality of fingerprint templates. When entering the fingerprint template registration process, the application processor 121 can be connected to the interface module 105, and send an instruction to the fingerprint sensor 102 through the interface module 105, to cause the fingerprint sensor to acquire fingerprint data at a first frame rate for fingerprint template registration. Each frame of the fingerprint data can be transmitted to the application processor 121 through the interface module 105.

[0070] In the embodiment of the present disclosure, in the electronic device 100, the application processor 121 can also display a visual prompt on the display screen 10 during the fingerprint template registration process. The visual prompt can include a prompt about the operation mode of the fingerprint template registration. As a typical implementation, the user can be prompted to press the finger on the fingerprint sensor 102 and move the finger during the pressing to make different fingerprint positions on the finger press on the fingerprint sensor 102, so that the fingerprint sensor 102 collects fingerprint images of multiple fingerprint positions. It should be understood that the embodiment of the present disclosure is not limited to the mode of continuous pressing and moving, but can also be a combination of continuous pressing and moving and pressing-lifting. Referring to FIG. 1B, the visual prompt can also include a prompt indicating the position of the fingerprint collection area. During the fingerprint template registration process, the visual prompt can also include registered fingerprint positions and unregistered fingerprint positions, so that the user moves the finger to make the fingerprint sensor 102 collect fingerprint images of unregistered fingerprint positions.

[0071] 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 at a first frame rate during the fingerprint template registration process. For ease of illustration, please refer to FIG. 1B. When the finger is pressed on the display screen 10 on the fingerprint collection area and moves, in order to improve the overall registration experience and reduce the registration time, the application processor 121 can set a higher first frame rate, and the first frame rate during the fingerprint template registration process is higher than the second frame rate during the fingerprint identification process. As a typical example, the application processor 121 can set the first frame rate during the fingerprint template registration process to be about 60 Hz-100 Hz, and the second frame rate during the fingerprint identification process to be 10 Hz. Moreover, the size of the first frame rate and the second frame rate can be set according to the actual product design needs.

[0072] In the embodiment of the present disclosure, the difference between the two different phase sub-data collected based on the same configuration in each frame of fingerprint data can reflect the motion state of the finger when collecting the frame of fingerprint data, and the motion state of the finger 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 different phase sub-data collected based on the same configuration to obtain the motion blur degree of the frame of fingerprint data. Motion blur refers to the phenomenon of fingerprint deformation, distortion and trailing during the movement of the finger, which can cause the collected fingerprint to be unmatched with the actual fingerprint. The motion blur degree can measure the possibility and degree of such phenomenon caused by the movement of the finger.

[0073] Further, in the embodiments of the present disclosure, the final fingerprint image can be generated according to at least part of the plurality of sub-data of different phases in a frame of fingerprint data, and the candidate fingerprint image for registration as a fingerprint template in the fingerprint template registration process. In the electronic device 100, the application processor 121 can perform fusion or the like on the plurality of sub-data of different phases to obtain the final fingerprint image.

[0074] As an implementation, 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 ultrasonic wave emitted by the fingerprint sensor 102, the phase of the received reflected wave can be controlled, so as to obtain a plurality of sub-data of a plurality of phases at a plurality of time points. For example, the sub-data of phase P1 is obtained at time t1 of frame F1, the sub-data of phase P2 is obtained at time t2, the sub-data of phase P3 is obtained at time t3, and so on, and the sub-data of phase Pi is obtained at time ti, so as to obtain i sub-data of i phases at i time points. i i Further, at time t i+1 , the sub-data of phase P i+1 is obtained. The time interval between t1 and t i+1 is the longest, and the sub-data of phase P1 and phase P i+1 is collected based on the same configuration. If the finger does not move substantially during t1 to t i+1 , the two sub-data are substantially identical, and if the finger moves during t1 to t i+1 , the difference between the two sub-data is positively correlated with the motion state of the finger. In step S202, the sub-data of phase P1 and phase P i+1 may be compared to obtain the motion blur degree of a frame of fingerprint data.

[0075] ​As an example, in the electronic device 100, a fingerprint image of any phase can be generated in the following manner. Specifically, the fingerprint sensor 102 is controlled to emit an ultrasonic signal corresponding to the phase, and the receiver array of the fingerprint sensor 102 detects a reflection signal formed by reflection off the finger and converts it into an electrical signal. Each receiver in the receiver array of the fingerprint sensor 102 corresponds to a specific spatial location, and the reflection signal at that location is recorded. The application processor 121 (or a separately provided analog-to-digital converter, etc.) can convert the electrical signal into a digital signal, and the application processor 121 can further convert the digital signal into a digital format that can be processed. Since the propagation speed of ultrasonic waves is different in different media, the received signals will have different phase shifts, and the application processor 121 can perform phase correction on these signals to ensure that the phase relationship between the signals is correct. 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 can be related to the phase or amplitude of the signal. Using the integrated signal, a fingerprint image at each receiver location can be reconstructed. This typically involves an inverse projection algorithm or beamforming technique, which projects the signal back to the surface of the finger to form a two-dimensional or three-dimensional fingerprint image. In the embodiments of the present disclosure, the phase shift used for phase correction and the integration time used for integration are substantially the same when generating the first fingerprint image and the second fingerprint image of the predetermined phase, so that the processing manner of the two is substantially the same.

[0076] Continuing with the above-described implementation, the above-described t1 to t i The multi-phase sub-data obtained is fused to highlight the fingerprint features and suppress noise. In the fingerprint template registration process, a candidate fingerprint image for registration as a fingerprint template is obtained after fusion. The fusion method can be a simple summation, weighted average, or a more complex image processing algorithm, and the embodiments of the present disclosure do not limit this.

[0077] In the above-described implementation, the more phases there are in theory, the more accurate the final fingerprint image generated based on the multi-phase fingerprint image is, but the more phases there are, the longer it takes to generate a frame of fingerprint data, which affects the frame rate. Considering that sliding registration has a greater impact on the frame rate, part of the performance can be sacrificed, and fewer phases are used. As a typical implementation, a frame of fingerprint data includes fingerprint images of two phases of phase0 and phase1, plus one fingerprint image of phase2 configured the same as phase0, a total of three phases of fingerprint images at three time points. It should be understood that in a specific implementation, the number of phases can be set according to the actual product design needs to meet the design needs of the frame rate, fingerprint image quality, etc.

[0078] In step S202, differences between two sub-data of different phases acquired based on the same configuration are compared to obtain the motion blur degree of the frame fingerprint data.

[0079] In an embodiment of the present disclosure, in the electronic device 100, after the application processor 121 acquires the frame fingerprint data generated by the fingerprint sensor 102, differences between two sub-data of different phases acquired based on the same configuration in the frame fingerprint data can be compared to obtain the motion blur degree of the frame fingerprint data. The sub-data contained in each frame 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 motion state. For example, the sub-data at the earliest time and the sub-data at the latest time in each frame fingerprint data can be selected for comparison to obtain the motion blur degree of the frame fingerprint data.

[0080] As an implementation, comparing the differences between two sub-data of different phases acquired based on the same configuration to obtain the motion blur degree 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; and determining the motion blur degree of the frame fingerprint data according to the dispersion. The dispersion of the difference map in the spatial domain can be the statistical variance, statistical standard deviation, etc. of each pixel in the difference map.

[0081] The size of the above dispersion is affected by the finger pressing force, the ridge line and valley line distinction degree of the fingerprint, etc. For example, the calculated dispersion can be different for the same finger of the same user with different pressing forces; the calculated dispersion can be different for different fingers (of the same user or different users) with different ridge line and valley line distinction degrees of the fingerprint. If the dispersion is directly used as the motion blur degree, it is difficult to unify the standard for fingerprint template registration based on the motion blur degree, i.e., one standard cannot adapt to different pressing forces and ridge line and valley line distinction degrees of the fingerprint. Considering that the finger pressing force and the ridge line and valley line distinction degree of the fingerprint cause different signal amounts of the fingerprint image, as a further implementation, determining the motion blur degree of the frame fingerprint data according to the dispersion specifically includes: determining the signal amount of the candidate fingerprint image, and normalizing the dispersion according to the signal amount to obtain the motion blur degree of the frame fingerprint data. The normalized dispersion as the motion blur degree is basically independent of the finger pressing force and the ridge line and valley line distinction degree of the fingerprint, which facilitates setting the standard for fingerprint template registration based on the motion blur degree.

[0082] The quality of the candidate fingerprint image generated according to the fingerprint data is affected by the pressing force of the finger, the distinctness of the ridge lines and valley lines of the fingerprint, etc. If the ridge lines and valley lines of the fingerprint are distinct and the pressing force is appropriate, the quality of the candidate fingerprint image is still high even if the finger movement is obvious (e.g., the sliding amplitude is large). When the finger movement is obvious, the motion blur obtained in step S201 is usually high, which may result in discarding the candidate fingerprint image with high quality, thereby reducing the efficiency of the fingerprint template registration and increasing the time length of the fingerprint template registration. Therefore, as a further implementation, the image quality score of the candidate fingerprint image can also be determined, and 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, and when the fingerprint template registration is performed based on the motion blur, the candidate fingerprint image with high image quality score can be avoided from being discarded, thereby improving the efficiency of the fingerprint template registration and reducing the time length of the fingerprint template registration.

[0083] In the above implementation, for a user with good fingerprint condition (distinct ridge lines and valley lines of the fingerprint), even if the finger movement is obvious (the motion blur before adjustment is high) during the registration process, the candidate fingerprint image with high image quality score can still be obtained, and the adjusted motion blur comprehensively considers the image quality score and the motion blur, which can avoid discarding the candidate fingerprint image with high image quality score, so that the user can quickly slide the finger to quickly collect the high-quality fingerprint image of the effective fingerprint position of the finger and quickly complete the fingerprint template registration. For a user with poor fingerprint condition (non-distinct ridge lines and valley lines of the fingerprint), the user can slowly slide the finger to perform the fingerprint template registration.

[0084] As a further typical implementation, the above adjustment of 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 proportion corresponding to the image quality score interval. For example, 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 by a first proportion; 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 by a second proportion, and the first proportion is greater than the second proportion; and if the image quality score is less than the second score threshold, the motion blur is kept unchanged. It should be understood that more or fewer score thresholds can be set in the embodiments of the present disclosure, and the more the score thresholds, the more accurate the adjustment of the motion blur based on the image quality score.

[0085] The above typical process of obtaining the motion blur degree can be summarized by the flow chart shown in FIG. 3. FIG. 3 shows a flow chart of a motion blur degree determination method according to an exemplary embodiment of the present disclosure. As shown in FIG. 3, the method of obtaining the motion blur degree according to the embodiment of the present disclosure includes steps S301 to S309.

[0086] In step S301, a difference map between two sub-data of different phases based on the same configuration acquisition in a frame of fingerprint data is determined.

[0087] For example, a frame of fingerprint data includes two phases of phase0 and phase1, and one more phase2 configured with phase0. The difference map between the fingerprint image of phase0 and the fingerprint image of phase2 in the frame of fingerprint data is determined.

[0088] In step S302, the dispersion of the difference map in the spatial domain is determined. Specifically, the dispersion of the difference map in the spatial domain can be the statistical variance, the statistical standard deviation, etc. of each pixel in the difference map.

[0089] In step S303, a candidate fingerprint image for registration as a fingerprint template is generated based on the frame of fingerprint data.

[0090] In step S304, the signal quantity and the image quality score of the candidate fingerprint image are determined.

[0091] In step S305, the dispersion is normalized according to the signal quantity to obtain a normalized dispersion, and an initial motion blur degree is obtained.

[0092] In step S306, the image quality score is compared with a first quality score threshold and a second quality score threshold. If the image quality score is greater than or equal to the first score threshold, step S307 is entered; if the image quality score is less than the first score threshold and greater than or equal to the second score threshold, step S308 is entered; if the image quality score is less than the second score threshold, step S309 is entered.

[0093] In step S307, the initial motion blur degree is reduced by a first proportion to obtain the motion blur degree.

[0094] In step S308, the initial motion blur degree is reduced by a second proportion to obtain the motion blur degree.

[0095] Wherein, the first proportion is greater than the second proportion.

[0096] In step S309, the initial motion blur degree is kept unchanged to obtain the motion blur degree. That is, if the image quality score is less than the second score threshold, the adjustment proportion is 1.

[0097] For example, the first quality score threshold is 50, and the second quality score threshold is 35. The initial motion blur degree is represented as S0, and the motion blur degree is represented as S. If the image quality score is greater than or equal to 50, the initial motion blur degree is reduced by 5 times, that is, S = S0 / 5. If the image quality score is less than 50 and greater than or equal to 35, the initial motion blur degree is reduced by 2 times, that is, S = S0 / 2. If the image quality score is less than 35, the initial motion blur degree is kept unchanged, that is, S = S0.

[0098] The motion blur degree is obtained in the manner shown in FIG. 3, the dispersion degree is normalized according to the signal quantity of the candidate fingerprint image, and the normalized dispersion degree is used as the initial motion blur degree, which is basically irrelevant to the pressing force of the finger and the distinction degree of the fingerprint ridge and valley, and is convenient for setting the standard for registering the fingerprint template based on the motion blur degree. The initial motion blur degree is adjusted according to the image quality score of the candidate fingerprint image, and the adjusted motion blur degree comprehensively considers the image quality score and the motion blur degree, which can avoid discarding the candidate fingerprint image with a high image quality score, improve the probability of passing the motion blur judgment for the high-quality candidate fingerprint image, and reduce the registration time of the fingerprint template.

[0099] In step S203, the fingerprint template is registered according to the motion blur degree of the frame fingerprint data.

[0100] In the embodiments of the present disclosure, whether the candidate fingerprint image corresponding to the fingerprint data is registered as a template can be determined based on the motion blur degree of the frame fingerprint data. In some embodiments, it can be further determined whether the candidate fingerprint image is registered as a template of which type.

[0101] As an implementation, the registering the fingerprint template according to the motion blur degree of the frame fingerprint data specifically includes: classifying the fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame fingerprint data; and registering the fingerprint template according to the motion blur type of the frame fingerprint data. The motion blur type can include a non-blur type and a full-blur type. In some implementations, if the motion blur type is the non-blur type, the corresponding candidate fingerprint image is registered as a fingerprint template; if the motion blur type is the full-blur type, 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 can include a non-blur type, a semi-blur type and a full-blur type, if the motion blur type is the non-blur type, the corresponding candidate fingerprint image is registered as a first type of fingerprint template; if the motion blur type is the semi-blur type, the corresponding candidate fingerprint image is registered as a second type of fingerprint template; if the motion blur type is the full-blur type, the corresponding fingerprint data is discarded, i.e., the candidate fingerprint image is not registered as a fingerprint template. The second type of fingerprint template is used to assist the first type of fingerprint template in fingerprint matching. Specifically, the first type of fingerprint template can be a strong fingerprint template, and the second type of fingerprint template can be a weak fingerprint template. The strong fingerprint template can be used for fingerprint matching alone, and the weak fingerprint template can assist fingerprint matching but not be used for fingerprint matching alone.

[0102] As an implementation, the classifying the fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame fingerprint data specifically includes: if the motion blur degree is less than or equal to a first motion blur degree threshold, determining that the motion blur type of the fingerprint data is a non-blur type, i.e., the fingerprint pattern is basically not blurred by the motion of the finger, and the fingerprint pattern is basically normal; if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to a second motion blur degree threshold, determining that the motion blur type of the fingerprint data is a semi-blur type, i.e., the fingerprint pattern is slightly deformed by the motion of the finger; and if the motion blur degree is greater than the second motion blur degree threshold, determining that the motion blur type of the fingerprint data is a full-blur type, i.e., the fingerprint pattern is abnormal by the motion of the finger.

[0103] In the embodiments of the present disclosure, before the candidate fingerprint image is registered as a fingerprint template, it can also be determined 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. As an implementation, 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 can 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; and 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 type of fingerprint template; and when the motion blur type is a semi-blur type, the corresponding candidate fingerprint image is registered as a second type of fingerprint template.

[0104] In the embodiments of the present disclosure, it is determined whether the registered first type of fingerprint template reaches a quantity threshold; if the registered first type of fingerprint template reaches the quantity threshold, the fingerprint template registration is ended; and if the registered first type of fingerprint template does not reach the quantity threshold, the fingerprint sensor continues to collect fingerprint data at the first frame rate to continue the fingerprint template registration.

[0105] The above typical process of fingerprint template registration according to the motion blur degree of each frame of fingerprint data can be summarized by the flowchart shown in FIG. 4. FIG. 4 shows a flowchart of a method of fingerprint template registration according to the motion blur degree according to an exemplary embodiment of the present disclosure. As shown in FIG. 4, the method of fingerprint template registration according to the motion blur degree of each frame of fingerprint data in the embodiments of the present disclosure includes steps S401 to S407.

[0106] In step S401, the motion blur degree of each frame of fingerprint data is compared with a first motion blur degree threshold and a second motion blur degree threshold. The motion blur degree can be determined based on the embodiments of the present disclosure, for example, by using the method shown in FIG. 3, which is not described herein.

[0107] If the motion blur degree is less than or equal to the first motion blur degree threshold, it is determined that the motion blur type of the frame of fingerprint data is a non-blur type, and step S402 is entered; if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to the second motion blur degree threshold, it is determined that the motion blur type of the frame of fingerprint data is a semi-blur type, and step S403 is entered; and if the motion blur degree is greater than the second motion blur degree threshold, it is determined that the motion blur type of the frame of fingerprint data is a full-blur type, and the frame of fingerprint data is not registered as a fingerprint template, and the fingerprint sensor continues to collect fingerprint data at the first frame rate to continue the fingerprint template registration.

[0108] Step S402, judging whether to register the candidate fingerprint image as a fingerprint template according to the image quality score and the effective area of the candidate fingerprint image corresponding to the frame fingerprint data. If yes, go to step S404. Otherwise, do not register as a fingerprint template, and continue to collect fingerprint data through the fingerprint sensor at the first frame rate to continue the fingerprint template registration.

[0109] Step S403, judging whether to register the candidate fingerprint image as a fingerprint template according to the image quality score and the effective area of the candidate fingerprint image corresponding to the frame fingerprint data. If yes, go to step S405. Otherwise, do not register as a fingerprint template, and continue to collect fingerprint data through the fingerprint sensor at the first frame rate to continue the fingerprint template registration.

[0110] Step S404, registering the candidate fingerprint image corresponding to the frame fingerprint data as a strong template.

[0111] Step S405, registering the candidate fingerprint image corresponding to the frame fingerprint data as a weak template.

[0112] Step S406, judging whether the number of registered strong templates reaches a number threshold. If the number of registered strong templates reaches the number threshold, go to step S407. If the number of registered strong templates does not reach the number threshold, continue to collect fingerprint data through the fingerprint sensor at the first frame rate to continue the fingerprint template registration.

[0113] Step S407, packaging the fingerprint template to complete the registration.

[0114] The fingerprint processing method of the embodiments of the present disclosure can improve the registration experience and reduce the registration time by collecting fingerprint images at a high frame rate during the fingerprint template registration process by using a finger sliding motion for registration. In order to ensure the quality of the fingerprint images during the finger motion, the difference between two sub-data of different phases based on the same configuration in a frame of fingerprint data is compared to determine the finger motion state during data collection. The fingerprint data frame with no motion or insignificant motion can be filtered out, which improves the registration experience without affecting the image quality of the template and thus does not affect the recognition success rate. When the finger moves while covering the fingerprint position on the screen, the frame rate is higher than that in the fingerprint recognition process to improve the overall registration experience and reduce the registration time. Considering the large difference in finger motion speed among users, it is impossible to avoid collecting deformed fingerprint signals all the time. The registration template area does not match the actual fingerprint, which seriously affects the recognition efficiency. Therefore, the useful signals that are basically consistent with the actual fingerprint are filtered out, and the selection of effective signals for data processing greatly improves the recognition accuracy.

[0115] The embodiment of the present disclosure further provides a fingerprint processing device, as shown in Figure 5, the fingerprint processing device provided by the embodiment of the present disclosure can include: a collection module 501 and a registration module 502. The collection module 501 is configured to collect fingerprint data by a fingerprint sensor at a first frame rate during a fingerprint template registration process, and each frame of the fingerprint data includes a plurality of different phase sub-data, at least two of the plurality of different phase sub-data being collected based on the same configuration. The registration module 502 is configured to compare the difference between the two different phase sub-data collected based on the same configuration to obtain the motion blur degree of the frame of fingerprint data; and perform fingerprint template registration according to the motion blur degree of the frame of fingerprint data.

[0116] In some embodiments, the registration module 502 can be specifically configured to determine a difference map of the two different phase sub-data collected based on the same configuration, determine the dispersion of the difference map in a spatial domain, and determine the motion blur degree of the frame of fingerprint data according to the dispersion.

[0117] In some embodiments, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame of fingerprint data. Further, the registration module 502 can be specifically configured to determine a signal amount of the candidate fingerprint image, normalize the dispersion according to the signal amount to obtain the motion blur degree of the frame of fingerprint data.

[0118] In some embodiments, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame of fingerprint data. Further, the registration module 502 can be specifically configured to determine an image quality score of the candidate fingerprint image, and adjust the motion blur degree according to the image quality score, wherein the motion blur degree is negatively correlated with the image quality score.

[0119] As an embodiment, the registration module 502 can 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 degree according to a proportion corresponding to the image quality score interval.

[0120] As an embodiment, the registration module 502 can be specifically configured to classify the fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame of fingerprint data, and perform fingerprint template registration according to the motion blur type of the frame of fingerprint data, wherein the motion blur type includes a non-blur type and a full-blur type.

[0121] As an implementation, the registration module 502 can be specifically configured to: if the motion blur degree is less than or equal to a first motion blur degree threshold, determine the motion blur type of the frame fingerprint data as a non-blurred type; if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to a second motion blur degree threshold, determine the motion blur type of the frame fingerprint data as a semi-blurred type; and if the motion blur degree is greater than the second motion blur degree threshold, determine the motion blur type of the frame fingerprint data as a fully-blurred type.

[0122] As an implementation, the registration module 502 is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data. Further, the registration module 502 can be specifically configured to: if the type of the fingerprint image is the semi-blurred type or the non-blurred type, determine whether to register the candidate fingerprint image as the fingerprint template according to the image quality score and / or the effective area of the candidate fingerprint image.

[0123] Further, the registration module 502 can be specifically configured to: if the motion blur type of the frame fingerprint data is the non-blurred type, perform a first type of fingerprint template registration according to the frame fingerprint data; and if the motion blur type of the frame fingerprint data is the semi-blurred type, perform a second type of fingerprint template registration according to the frame fingerprint data.

[0124] In some embodiments, the fingerprint processing apparatus can form a fingerprint identification system inside the electronic device 100 together with the fingerprint sensor 102 shown in FIGS. 1A, 1B and 1C, where the fingerprint processing apparatus can specifically be the fingerprint processing apparatus shown in FIGS. 1B and 1C, which can be configured in an application processor 121 (such as a central processing unit CPU) of the electronic device 100, for performing the main steps of the fingerprint processing method described in the above various embodiments. In other alternative embodiments, the fingerprint processing apparatus can also be implemented by other processing units or control units (such as a microcontroller MCU) with image processing capabilities.

[0125] In some embodiments, the fingerprint processing apparatus can be implemented by modules as shown in FIG. 6. As shown in FIG. 6, 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, the ultrasonic fingerprint sensor 601 generates and receives signals through the controller 602, the digital-to-analog conversion is completed through the ultrasonic fingerprint sensor 601, the data rearrangement and packaging are completed through the data processor 603, the converted data is sent to the algorithm processor 605 for algorithm processing, and the fingerprint template registration and identification are completed. The algorithm processor 605 can perform the main steps of the fingerprint processing method described in the above various embodiments. The controller 602, the data processor 603, the analog-to-digital converter 604, and the algorithm processor 605 can be an implementation of the control system 120 shown in FIG. 1C. The functions of the fingerprint processing apparatus are split into the controller 602, the data processor 603, the analog-to-digital converter 604, and the algorithm processor 605 for implementation.

[0126] In the ultrasonic fingerprint system, sliding fingerprint template registration is implemented. Benefiting from the higher acquisition frame rate of the ultrasonic fingerprint sensor 601 processing ultrasonic signals, in the ultrasonic fingerprint template registration process, unlike the traditional finger pressing registration mode, a finger sliding motion mode can be used for registration, the fingerprint signal is collected by increasing the ultrasonic signal frame rate, thereby improving the registration experience and reducing the registration time. In order to ensure the quality of the fingerprint image during the motion, the difference between the fingerprint images at different time points during the finger motion is compared to judge the finger motion state during data acquisition, which can be used to filter out image signals without obvious motion, improve the registration experience without affecting the image quality of the template, thereby not affecting the identification success rate. Compared with other pressing and lifting template registration schemes, the ultrasonic signal frame rate is higher, and more data can be collected in a short time even in motion, so it is easier to obtain images without motion blur, and the signal collection of the finger fingerprint position can be effectively completed in a shorter time, thereby improving the fingerprint template registration experience and efficiency.

[0127] Embodiments of the present disclosure also provide an electronic device 100, which includes a device body 101 and the above-mentioned fingerprint sensor 102 arranged on the device body 101. In some embodiments, the electronic device 100 can be a portable electronic device, which can be a smartphone, a tablet computer, a notebook computer, a personal digital assistant, etc. Alternatively, the electronic device 100 can also be a smart wearable device, and embodiments of the present disclosure do not limit this.

[0128] The electronic device 100 provided by the embodiments of the present disclosure can further include an application processor 121; and a memory storing a program, wherein the program includes instructions that, when executed by the application processor 121, cause the application processor 121 to perform the method of the above embodiments, such as the method shown in FIGS. 2-4.

[0129] The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the application processor 121 of the electronic device 100 to perform the method of the above embodiments, such as the method shown in FIGS. 2-4.

[0130] Referring to FIG. 7, which is a structural block diagram of an electronic device 700 provided by the embodiments of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device 700 can include a computing unit 701 that 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 into a random access memory (RAM) 703 from a storage unit 708. In the RAM 703, various programs and data required for the operation of the electronic device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0131] A plurality of components in the electronic device 700 are connected to the I / O interface 705, including an input unit 706, an output unit 707, a storage unit 708, and a communication unit 709. The input unit 706 can be any type of device capable of inputting information to the electronic device 700, and can receive inputted digital or character information, and generate key signal inputs related to user settings and / or function controls of the electronic device. The output unit 707 can be any type of device capable of presenting information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 708 can include but is not limited to a magnetic disk, an optical disk. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunications networks, and can 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.

[0132] The computing unit 701 can be various general and / or special purpose processing components 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 various methods and processes described in the present disclosure. For example, in some embodiments, the fingerprint processing method of the present embodiments 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 onto 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 the method of the present embodiments by any suitable means, such as by means of firmware.

[0133] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, and partially on a remote machine or entirely on a remote machine or server.

[0134] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable storage media can include, without limitation, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media can include one or more lines of electrical connections, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical storage devices, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0135] 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., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal that can be used to provide machine instructions and / or data to a programmable processor.

[0136] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device for displaying information to the user and a keyboard and a pointing device, e.g., a mouse, trackball, etc., by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; 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, speech, or tactile input.

[0137] The above merely provides the preferred embodiment of the present disclosure and does not limit the present disclosure in any form. Although the present disclosure has been disclosed as above with the preferred embodiment, it is not intended to limit the present disclosure. Any person skilled in the art can make some minor changes or modifications to the equivalent embodiments with the disclosed technical content without departing from the technical solution of the present disclosure. Any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present disclosure are still within the scope of the technical solution of the present disclosure.

Claims

1. A method of fingerprint processing, characterized by, Comprise: In the fingerprint template registration process, the fingerprint data is collected by the fingerprint sensor according to a first frame rate, and each frame of fingerprint data comprises a plurality of different phase sub-data, at least two of which are collected based on the same configuration; Compare the difference between the two different phase sub-data collected based on the same configuration to obtain the motion blur degree of the frame fingerprint data; According to the motion blur degree of the frame fingerprint data, the fingerprint template registration is carried out.

2. The method of claim 1, wherein, Said comparison of the difference between the two different phase sub-data collected based on the same configuration to obtain the motion blur degree of the frame fingerprint data comprises: Determine the difference map between the two different phase sub-data collected based on the same configuration; Determine the dispersion of the difference map in the spatial domain; According to the dispersion, the motion blur degree of the frame fingerprint data is determined.

3. The method of claim 2, wherein, Also include: According to the frame fingerprint data, a candidate fingerprint image for registration as a fingerprint template is determined; Said determination of the motion blur degree of the frame fingerprint data according to the dispersion comprises: Determine the signal quantity of the candidate fingerprint image; According to the signal quantity, the dispersion is normalized to obtain the motion blur degree of the frame fingerprint data.

4. The method of claim 2, wherein, Also include: According to the frame fingerprint data, a candidate fingerprint image for registration as a fingerprint template is determined; Said comparison of the difference between the two different phase sub-data collected based on the same configuration to obtain the motion blur degree of the frame fingerprint data further comprises: Determine the image quality score of the candidate fingerprint image; According to the image quality score, the motion blur degree is adjusted, wherein the motion blur degree is negatively correlated with the image quality score.

5. The method of claim 4, wherein, According to the image quality score, the motion blur degree is adjusted, comprising: 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; Adjust the motion blur degree according to the proportion corresponding to the image quality score interval.

6. The method of claim 5, wherein: If the image quality score is greater than or equal to a first score threshold, the motion blur degree is reduced by a first proportion; 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 degree is reduced by a second proportion, the first proportion being greater than the second proportion; If the image quality score is less than the second score threshold, the motion blur degree is kept unchanged.

7. The method of claim 1, wherein, Said registration of the fingerprint template according to the motion blur degree of the frame fingerprint data comprises: Classify the frame fingerprint data according to at least one motion blur degree threshold to obtain the motion blur type of the frame fingerprint data, the motion blur type comprising a non-blur type and a full-blur type; According to the motion blur type of the frame fingerprint data, the fingerprint template registration is carried out.

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

9. The method of claim 8, wherein, Further comprising: determining a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data; the fingerprint template registration according to the motion blur type of the frame fingerprint data comprises: if the type of the fingerprint image is the semi-blur type or the non-blur type, determining whether to register the candidate fingerprint image as a fingerprint template according to an image quality score and / or an effective area of the candidate fingerprint image.

10. The method of 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 comprises: 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 an 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.

11. The method of any one of claims 7 to 10, wherein, the fingerprint template registration according to the motion blur type of the frame fingerprint data comprises: if the motion blur type of the frame fingerprint data is the non-blur type, performing a first type of fingerprint template registration according to the frame fingerprint data; if the motion blur type of the frame fingerprint data is the semi-blur type, performing a second type of fingerprint template registration according to the frame fingerprint data.

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

13. The method of claim 11, wherein, Further comprising: determining whether the registered first type of fingerprint template reaches a quantity threshold; if the registered first type of fingerprint template reaches the quantity threshold, ending the fingerprint template registration; if the registered first type of fingerprint template does not reach the quantity threshold, continuing the step of collecting fingerprint data by the fingerprint sensor at the first frame rate.

14. The method of claim 1, wherein, Further comprising: in a fingerprint recognition process, collecting fingerprint data by the fingerprint sensor at a second frame rate, wherein the first frame rate is greater than the second frame rate.

15. The method of claim 1, wherein, the fingerprint template registration process comprises a process in which a finger continuously contacts and moves with a fingerprint collection area, and the movement is used to change a fingerprint position of the finger contacting the fingerprint collection area.

16. The method of claim 1, wherein, the fingerprint sensor comprises an ultrasonic fingerprint sensor.

17. A fingerprint processing device, characterized by Comprising: a collection module, configured to collect fingerprint data by a fingerprint sensor at a first frame rate in a fingerprint template registration process, and each frame of the fingerprint data comprises a plurality of different phase sub-data, and at least two of the plurality of different phase sub-data are collected based on a same configuration; a registration module, configured to compare differences between two different phase sub-data collected based on the same configuration to obtain a motion blur degree of the frame fingerprint data; performing fingerprint template registration according to the motion blur degree of the frame fingerprint data.

18. The apparatus of claim 17, wherein, The registration module is configured to determine a difference map of two different phase sub-data collected based on the same configuration, determine a dispersion of the difference map in a spatial domain, and determine a motion blur degree of the frame fingerprint data according to the dispersion.

19. The apparatus of claim 18, wherein, The registration module is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data, and determine a signal quantity of the candidate fingerprint image; and normalize the dispersion according to the signal quantity to obtain the motion blur degree of the frame fingerprint data.

20. The apparatus of claim 18, wherein, The registration module is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data, and determine an image quality score of the candidate fingerprint image; and adjust the motion blur degree according to the image quality score, wherein the motion blur degree is negatively correlated with the image quality score.

21. The apparatus of claim 20, 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 degree according to a proportion corresponding to the image quality score interval.

22. The apparatus of claim 17, wherein, The registration module is configured to classify the frame fingerprint data according to at least one motion blur degree threshold to obtain a motion blur type of the frame fingerprint data, wherein the motion blur type includes a non-blur type and a full-blur type, and perform fingerprint template registration according to the motion blur type of the frame fingerprint data.

23. The apparatus of claim 21, wherein, The registration module is configured to determine that the motion blur type of the frame fingerprint data is the non-blur type if the motion blur degree is less than or equal to a first motion blur degree threshold, determine that the motion blur type of the frame fingerprint data is a half-blur type if the motion blur degree is greater than the first motion blur degree threshold and less than or equal to a second motion blur degree threshold, and determine that the motion blur type of the frame fingerprint data is the full-blur type if the motion blur degree is greater than the second motion blur degree threshold.

24. The apparatus of claim 22, wherein, The registration module is further configured to determine a candidate fingerprint image for registration as a fingerprint template according to the frame fingerprint data, and determine whether to register the candidate fingerprint image as a fingerprint template according to an image quality score and / or an effective area of the candidate fingerprint image if the type of the fingerprint image is the half-blur type or the non-blur type.

25. The apparatus of claim 22, wherein, The registration module is configured to perform a first type of fingerprint template registration according to the frame fingerprint data if the motion blur type of the frame fingerprint data is the non-blur type, and perform a second type of fingerprint template registration according to the frame fingerprint data if the motion blur type of the frame fingerprint data is the half-blur type.

26. An electronic device, comprising: The fingerprint sensor comprises an ultrasonic fingerprint sensor. 28.An electronic device comprising: a processor; 27. The electronic device of claim 26, wherein, and a memory storing a program, wherein the program includes instructions that, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 16. ​ ​ ​ 29. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are for causing a computer to perform the method according to any one of claims 1 to 16. The computer instructions are for causing a computer to perform the method according to any one of claims 1 to 16.

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