CN110378263B - Fingerprint identification method and related product - Google Patents
Fingerprint identification method and related product Download PDFInfo
- Publication number
- CN110378263B CN110378263B CN201910610655.3A CN201910610655A CN110378263B CN 110378263 B CN110378263 B CN 110378263B CN 201910610655 A CN201910610655 A CN 201910610655A CN 110378263 B CN110378263 B CN 110378263B
- Authority
- CN
- China
- Prior art keywords
- fingerprint
- layer
- picture data
- fingerprint picture
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/13—Sensors therefor
- G06V40/1306—Sensors therefor non-optical, e.g. ultrasonic or capacitive sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
Abstract
The embodiment of the application discloses fingerprint identification method and related product, electronic equipment includes ultrasonic fingerprint identification module, and wherein the method includes: when receiving a fingerprint to-be-acquired instruction, acquiring at least one layer of fingerprint picture data of a target object; matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result; and when the matching result is determined to be matching, determining that the fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification. By adopting the embodiment of the application, the identification speed is high, and the user experience is improved.
Description
Technical Field
The application relates to the technical field of electronic equipment, in particular to a fingerprint identification method and a related product.
Background
With the widespread use of electronic devices (such as mobile phones, tablet computers, and the like), the electronic devices have more and more applications and more powerful functions, and the electronic devices are developed towards diversification and personalization, and become indispensable electronic products in the life of users.
Fingerprint identification technology also becomes the standard configuration technology of electronic equipment, and along with fingerprint identification technology's development, seeing at present, ultrasonic fingerprint identification technology is more and more receiving the favor of supplier, but ultrasonic fingerprint identification speed is slow, influences user experience degree.
Disclosure of Invention
The embodiment of the application provides a fingerprint identification method and a related product, which can improve the speed of ultrasonic fingerprint identification and improve the user experience.
In a first aspect, an embodiment of the present application provides an electronic device, which includes a processing circuit and an ultrasonic fingerprint identification module connected to the processing circuit, wherein,
the processing circuit is used for starting the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the ultrasonic fingerprint identification module is used for collecting at least one layer of fingerprint picture data of a target object;
the processing circuit is used for matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result, when the matching result is determined to be matched, determining that fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification.
In a second aspect, a fingerprint identification method is provided, which is applied to an electronic device, where the electronic device includes an ultrasonic fingerprint identification module; the method comprises the following steps:
when receiving a fingerprint to-be-acquired instruction, acquiring at least one layer of fingerprint picture data of a target object;
matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result;
and when the matching result is determined to be matching, determining that the fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification.
In a third aspect, a fingerprint identification apparatus is provided, which is applied to an electronic device, where the electronic device includes an ultrasonic fingerprint identification module; the device comprises: an acquisition unit, a matching unit, an execution unit, wherein,
the acquisition unit is used for acquiring at least one layer of fingerprint image data of a target object through the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the matching unit is used for matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result;
and the execution unit is used for determining that the fingerprint verification is successful and executing the operation corresponding to the successful fingerprint verification when the matching result is determined to be matching.
In a fourth aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the second aspect of the embodiment of the present application.
In a fifth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform some or all of the steps described in the second aspect of the present application.
In a sixth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the second aspect of embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that the technical scheme that this application provided is when receiving the fingerprint and treating the collection instruction, through at least one deck fingerprint picture data of ultrasonic fingerprint identification module collection, when confirming that fingerprint verification passes, carries out the operation that corresponds with this fingerprint verification success. According to the technical scheme, only at least one layer of fingerprint picture data is matched and collected, after the matching is successful, the fingerprint pictures after at least one layer of fingerprint pictures can not be collected and matched, the times of fingerprint collection and the calculated amount of matching are reduced, and the speed of fingerprint unlocking is improved, so that the fingerprint identification method has the advantages of being high in fingerprint identification speed and improving user experience.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1A is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 1B is a schematic structural diagram of another electronic device provided in the embodiment of the present application;
fig. 1C is a schematic flowchart of a fingerprint identification method according to an embodiment of the present application;
fig. 1D is a schematic illustration of a fingerprint acquisition area provided in an embodiment of the present application;
FIG. 2 is a schematic flowchart of a fingerprint identification method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
FIG. 4A is a block diagram illustrating functional units of a fingerprint identification device according to an embodiment of the present disclosure;
fig. 4B is a block diagram illustrating functional units of another fingerprint identification device according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device related to the embodiments of the present application may include various handheld devices, vehicle-mounted devices, wearable devices (smart watches, smart bracelets, wireless headsets, augmented reality/virtual reality devices, smart glasses), computing devices or other processing devices connected to wireless modems, and various forms of User Equipment (UE), Mobile Stations (MS), terminal devices (terminal device), and the like, which have wireless communication functions. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices.
The following describes embodiments of the present application in detail.
Referring to fig. 1A, fig. 1A is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application, the electronic device 100 includes a storage and processing circuit 110, and a sensor 170 connected to the storage and processing circuit 110, where:
the electronic device 100 may include control circuitry, which may include storage and processing circuitry 110. The storage and processing circuitry 110 may be a memory, such as a hard drive memory, a non-volatile memory (e.g., flash memory or other electronically programmable read-only memory used to form a solid state drive, etc.), a volatile memory (e.g., static or dynamic random access memory, etc.), etc., and the embodiments of the present application are not limited thereto. Processing circuitry in storage and processing circuitry 110 may be used to control the operation of electronic device 100. The processing circuitry may be implemented based on one or more microprocessors, microcontrollers, digital signal processors, baseband processors, power management units, audio codec chips, application specific integrated circuits, display driver integrated circuits, and the like.
The storage and processing circuitry 110 may be used to run software in the electronic device 100, such as an Internet browsing application, a Voice Over Internet Protocol (VOIP) telephone call application, an email application, a media playing application, operating system functions, and so forth. Such software may be used to perform control operations such as, for example, camera-based image capture, ambient light measurement based on an ambient light sensor, proximity sensor measurement based on a proximity sensor, information display functionality based on status indicators such as status indicator lights of light emitting diodes, touch event detection based on a touch sensor, functionality associated with displaying information on multiple (e.g., layered) display screens, operations associated with performing wireless communication functionality, operations associated with collecting and generating audio signals, control operations associated with collecting and processing button press event data, and other functions in the electronic device 100, to name a few.
The electronic device 100 may include input-output circuitry 150. The input-output circuit 150 may be used to enable the electronic device 100 to input and output data, i.e., to allow the electronic device 100 to receive data from an external device and also to allow the electronic device 100 to output data from the electronic device 100 to the external device. The input-output circuit 150 may further include a sensor 170. Sensor 170 may include the ultrasonic fingerprint identification module, may also include ambient light sensor, proximity sensor based on light and electric capacity, touch sensor (for example, based on light touch sensor and/or capacitanc touch sensor, wherein, touch sensor may be a part of touch display screen, also can regard as a touch sensor structure independent utility), acceleration sensor, and other sensors etc., the ultrasonic fingerprint identification module can be integrated in the screen below, or, the ultrasonic fingerprint identification module can set up in electronic equipment's side or back, do not do the restriction here, this ultrasonic fingerprint identification module can be used to gather the fingerprint image.
Input-output circuit 150 may also include one or more display screens, such as display screen 130. The display 130 may include one or a combination of liquid crystal display, organic light emitting diode display, electronic ink display, plasma display, display using other display technologies. The display screen 130 may include an array of touch sensors (i.e., the display screen 130 may be a touch display screen). The touch sensor may be a capacitive touch sensor formed by a transparent touch sensor electrode (e.g., an Indium Tin Oxide (ITO) electrode) array, or may be a touch sensor formed using other touch technologies, such as acoustic wave touch, pressure sensitive touch, resistive touch, optical touch, and the like, and the embodiments of the present application are not limited thereto.
The electronic device 100 may also include an audio component 140. The audio component 140 may be used to provide audio input and output functionality for the electronic device 100. The audio components 140 in the electronic device 100 may include a speaker, a microphone, a buzzer, a tone generator, and other components for generating and detecting sound.
The communication circuit 120 may be used to provide the electronic device 100 with the capability to communicate with external devices. The communication circuit 120 may include analog and digital input-output interface circuits, and wireless communication circuits based on radio frequency signals and/or optical signals. The wireless communication circuitry in communication circuitry 120 may include radio-frequency transceiver circuitry, power amplifier circuitry, low noise amplifiers, switches, filters, and antennas. For example, the wireless Communication circuitry in Communication circuitry 120 may include circuitry to support Near Field Communication (NFC) by transmitting and receiving Near Field coupled electromagnetic signals. For example, the communication circuit 120 may include a near field communication antenna and a near field communication transceiver. The communications circuitry 120 may also include a cellular telephone transceiver and antenna, a wireless local area network transceiver circuitry and antenna, and so forth.
The electronic device 100 may further include a battery, power management circuitry, and other input-output units 160. The input-output unit 160 may include buttons, joysticks, click wheels, scroll wheels, touch pads, keypads, keyboards, cameras, light emitting diodes and other status indicators, and the like.
A user may input commands through input-output circuitry 150 to control the operation of electronic device 100, and may use output data of input-output circuitry 150 to enable receipt of status information and other outputs from electronic device 100.
In a possible example, taking the ultrasonic fingerprint identification module as an example below the screen, as shown in fig. 1B, fig. 1B is a schematic structural diagram of an electronic device, and the electronic device 100 may include a Glass Cover plate (Cover Glass)210, a display screen (OLED)220, an adhesion layer (Adhesive)230, a substrate (TFT Glass)240, a Pixel layer (Pixel)250, a piezoelectric material layer (polymer) 260, an Ag Ink layer 270, and a solidified Adhesive layer (DAF) 280. Of course, the glass cover plate may further include a film layer (film), which may be a tempered film for protecting the display screen of the electronic device.
Further, the ultrasonic fingerprint identification module can include: the TFT Glass layer, the Pixel layer, the Ag Ink layer and the solidification glue layer. The TFT Glass layer is used for metal wiring and material coating; the Pixel layer is used for embedding a Metal electrode on the TFT Glass, is used as a cathode for ultrasonic transmission/reception and is also called a piezoelectric transduction material, and can realize material deformation-voltage interconversion; an Ag Ink layer used as a positive electrode for ultrasonic transmission/reception; the DAF is a solidified glue and is used for protecting the ultrasonic fingerprint identification module; the Adhesive layer is formed by bonding the ultrasonic fingerprint identification module at the bottom of the OLED screen.
In a specific implementation, the ultrasonic fingerprint identification module may include 2 states, a TX state (for transmitting ultrasonic waves) and an RX state (for receiving ultrasonic waves).
In a TX state, high-frequency (usually 10MHz level) oscillation signals such as sine waves are provided through electrodes (a Pixel negative electrode and an Ag Ink positive electrode) at two ends of a Copolymer (piezoelectric material), the Copolymer can generate vibration of response frequency and emit ultrasonic waves, the ultrasonic waves transmitted upwards reach fingerprints in contact with the surface of a screen after penetrating through an OLED screen, and when fingerprint valley ridges are attached to the screen, the difference between the acoustic resistance characteristic of air in the fingerprint valleys and the acoustic resistance characteristic of glass on the surface of the screen is large, the difference between the acoustic resistance characteristic of skin tissues of the fingerprint ridges and the acoustic resistance characteristic of glass on the surface of the screen is large, so the intensity of ultrasonic reflection signals of the fingerprint valley ridges is different.
In an RX state, after reflected ultrasonic waves pass through the display screen again and reach the ultrasonic fingerprint identification module (Pixel-Copolymer-Ag Ink), the Copolymer is caused to vibrate to generate electric signals, the vibration intensity of the Copolymer in Pixel areas corresponding to fingerprint ridges at different positions is different, so that the potential differences received by the pixels at different positions are different (the Ag Ink is equal potential), the potential differences are converted into two-dimensional image signals, and an ultrasonic fingerprint image is obtained.
The electronic device described with reference to fig. 1A and 1B may be configured to implement the following functions:
the storage and processing circuit 110 is used for starting the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the ultrasonic fingerprint identification module is used for collecting at least one layer of fingerprint picture data of a target object;
and the storage and processing circuit 110 is configured to match the at least one layer of fingerprint image data with at least one layer of fingerprint image data of a preset module to determine a matching result, determine that the fingerprint verification is successful when the matching result is determined to be matching, and execute an operation corresponding to the successful fingerprint verification.
In an optional scenario, if the preliminary fingerprint picture is a multi-finger fingerprint picture, the storage and processing circuit 110 is specifically configured to:
and performing quality evaluation on the multilayer fingerprint image data to obtain a plurality of image quality evaluation values, selecting an ith layer fingerprint image with the best quality evaluation from the plurality of image instruction evaluation values, and matching the ith layer fingerprint image with an ith layer fingerprint image of a preset fingerprint module to obtain a matching result.
In an optional scenario, if the preliminary fingerprint picture is a multi-finger fingerprint picture, the storage and processing circuit 110 is specifically configured to:
the multilayer fingerprint image data and the multilayer fingerprint image data of the preset module are compared one by one, and the one by one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if the upper-layer fingerprint picture data of the multilayer fingerprint picture data are matched with the upper-layer fingerprint picture data of the preset module, ending the one-by-one comparison process, if the upper-layer fingerprint picture data are not matched with the preset module, continuing to perform comparison of the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched.
In an optional scenario, if the preliminary fingerprint picture is a multi-finger fingerprint picture, the storage and processing circuit 110 is specifically configured to:
and identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result.
In an alternative, the storage and processing circuit 110 is specifically configured to:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data;
the noise identification operation specifically includes: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the total area of the beta set intervals is the area of noise data.
Referring to fig. 1C, fig. 1C is a schematic flow chart of a fingerprint identification method according to an embodiment of the present application, and as shown in the drawing, the fingerprint identification method is applied to the electronic device shown in fig. 1A, the electronic device includes an ultrasonic fingerprint identification module, a fingerprint collection area is shown in fig. 1D, and the fingerprint identification method includes:
s101, when receiving a fingerprint to-be-acquired instruction, the electronic equipment acquires at least one layer of fingerprint image data of a target object through an ultrasonic fingerprint identification module;
the instruction to be acquired includes but is not limited to: a fingerprint to-be-unlocked instruction and a fingerprint to-be-allowed instruction. The fingerprint to-be-allowed instruction may specifically be an instruction for allowing entry to a certain app. The certain app includes but is not limited to: financial class apps, payment class apps, short message or instant messaging class apps, and the like.
The method for judging whether the electronic device receives the instruction to acquire the fingerprint includes, but is not limited to:
in an alternative embodiment, the distance of the target object may be determined by a distance sensor, and if the distance is within a first range, it is determined that a fingerprint to be acquired is received. Of course, the determination may also be performed in other manners, for example, by combining a pressure sensor and a temperature sensor, specifically, when the pressure value detected by the pressure sensor is zero but the temperature of the target object detected by the temperature sensor is a set temperature threshold, it is determined that the fingerprint to-be-acquired instruction is received. In practical applications, of course, other manners may also be used, for example, when the pressure sensor detects that the pressure value is greater than the set threshold, it is determined that the instruction to be acquired by the fingerprint is received.
In the embodiment of the present application, the target object may be a human or other animals. For example, different people have different physical conditions and different corresponding fingerprint collection parameters, and certainly, the same person has different corresponding fingerprint collection parameters due to differences between body parts (for example, different collection parameters are obtained for fingerprints of fingers and fingerprints of palms). The electronic device may pre-store a mapping relationship between a preset body part and a collection parameter, where each mapping relationship is a mapping relationship between a fingerprint collection part and a fingerprint collection parameter. In a specific implementation, the electronic device may obtain a target collection portion of a target object, and further determine a fingerprint collection parameter corresponding to the collection portion according to a corresponding relationship between a preset collection portion and a mapping relationship, and determine the collection portion of the target object, which may be identified by an image identification method, for example, collecting a fingerprint image and inputting the fingerprint image into a preset neural network model, so as to obtain the collection portion corresponding to the fingerprint image, since fingerprints of each portion of a human body have a certain similarity in general, the corresponding portion may be identified by the fingerprint image through the preset neural network model, of course, the collection portion may also be input by a user, the preset neural network model may be default by a system, and further, according to a target mapping relationship set, a first fingerprint collection parameter corresponding to the target fingerprint collection portion may be determined, therefore, reasonable fingerprint acquisition parameters can be selected according to the physiological condition and the acquisition part of the user, and the fingerprint image acquisition efficiency is improved. The collection part can be set by a user or defaulted by a system, and the collection part can be at least one of the following parts: fingers, palms, arms, thighs, neck, etc., without limitation thereto.
S102, the electronic equipment matches the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result;
optionally, there may be a plurality of specific implementation methods for determining the matching result by matching the at least one layer of fingerprint image data with the at least one layer of fingerprint image data of the preset module, for example, in an optional implementation scheme, the at least one layer of fingerprint image data is compared with a preset image of the template to determine a similarity, and whether the similarity is greater than a preset matching threshold is determined, if the similarity between the at least one layer of fingerprint image data and the image of the template is greater than the preset matching threshold, the matching result is determined to be a match.
The preset matching threshold may be dynamically adjusted according to an environmental parameter, where the environmental parameter may be at least one of the following: ambient brightness, ambient color temperature, humidity, temperature, geographical location, environmental background, etc. do not limit here, and in concrete implementation, electronic equipment may be provided with an environmental sensor, can gather environmental parameter based on environmental sensor, and environmental sensor may be at least one of following: an ambient light sensor, a color temperature sensor, a humidity sensor, a position sensor, an image sensor, and the like, without limitation. The preset quality evaluation value may be stored in the electronic device in advance, and may be set by the user or default by the system. The electronic device may also pre-store a mapping relationship between a preset environmental parameter and an optical fingerprint identification threshold. The preset pattern may be a nine-square grid, a four-square grid, a sixteen-square grid, or the like, which is not limited herein.
And step S103, when the electronic equipment determines that the matching result is matching, determining that the fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification.
The executing the operation corresponding to the successful fingerprint verification may specifically include:
the above-mentioned performing of the operation corresponding to the successful fingerprint verification may be different according to different device states, for example, in an alternative embodiment, if the device state is the screen locking state, the unlocking operation is performed. In another alternative embodiment, if the device status is instant messaging, an operation of displaying an instant messaging message is performed. In yet another alternative embodiment, if the device state is a financial app, then an enter allowed or payment operation is performed. Of course, in practical applications, the above device state change operation is not limited to the above example.
Wherein the unlocking operation can be at least one of the following: entering a main page by locking or blank screen, or starting a preset application by locking or blank screen, or executing a preset operation, wherein the preset operation can be at least one of the following operations: deletion operation, modification operation, compression operation, selection operation, photographing operation, payment operation, and the like, without limitation. The electronic equipment can perform unlocking operation when the matching value between the target fingerprint image and the preset fingerprint template is greater than the target fingerprint identification threshold, otherwise, prompt the user that the fingerprint unlocking is failed or prompt the user to perform fingerprint input again when the matching value between the target fingerprint image and the preset fingerprint template is less than or equal to the target fingerprint identification threshold.
The technical scheme that this application provided is when receiving the fingerprint and treating the instruction of gathering, gathers at least one deck fingerprint picture data through ultrasonic fingerprint identification module, and when confirming that fingerprint verification passes, execution and this fingerprint verification succeed in the operation that corresponds. According to the technical scheme, only at least one layer of fingerprint picture data is matched and collected, after the matching is successful, the fingerprint pictures after at least one layer of fingerprint pictures can not be collected and matched, the times of fingerprint collection and the calculated amount of matching are reduced, and the speed of fingerprint unlocking is improved, so that the fingerprint identification method has the advantages of being high in fingerprint identification speed and improving user experience.
Optionally, if the at least one layer of fingerprint image data includes multiple layers of fingerprint image data, the implementation method of step S102 may specifically include:
and performing quality evaluation on the multilayer fingerprint image data to obtain a plurality of image quality evaluation values, selecting an ith layer fingerprint image with the best quality evaluation from the plurality of image instruction evaluation values, and matching the ith layer fingerprint image with an ith layer fingerprint image of a preset fingerprint module to obtain a matching result.
According to the technical scheme, when the fingerprint image data with the best quality is provided with multiple layers of fingerprint image data, the fingerprint image data with the best quality evaluation is selected for matching, and the probability of successful matching of the fingerprint image data with the best quality evaluation is highest, so that the matching frequency is reduced as much as possible while the success rate is ensured, and the matching calculation amount is reduced.
Optionally, if the at least one layer of fingerprint image data includes multiple layers of fingerprint image data, the implementation method of step S102 may specifically include:
the multi-layer fingerprint image data and the multi-layer fingerprint image data of the preset module are subjected to one-by-one comparison process, and the one-by-one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if matching, ending the one-by-one comparison process, if not matching, continuing to compare the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched, and ending the one-by-one comparison process.
Optionally, if the at least one layer of fingerprint image data includes multiple layers of fingerprint image data, the implementation method of step S102 may specifically include:
and identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the minimum noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result.
The above noise data areas include, but are not limited to: a spot data area, a scar data area, or a blocked data area.
The above implementation method for identifying and determining multiple noise data areas corresponding to the multi-layer fingerprint image data for each layer of fingerprint image data in the multi-layer fingerprint image data may specifically include:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data; the noise identification operation may specifically include: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the areas of the beta set intervals are noise data areas.
The characteristic of realizing the area of the noise data is that the noise data does not have characteristic points, and the distribution of the characteristic points of the fingerprint is uniform, the whole fingerprint picture data is divided into a plurality of set intervals, if the set intervals do not contain the characteristic points, the set intervals can be determined to be noise intervals, and the areas of all the noise intervals are superposed to obtain the area of the noise data.
Optionally, the electronic device matches the at least one layer of fingerprint image data with the at least one layer of fingerprint image data of the preset module to determine a matching result, as shown in fig. 2, the method may include the following steps:
s201, carrying out image segmentation on a first layer of fingerprint image in at least one layer of fingerprint image data to obtain a target fingerprint area image;
s202, analyzing the distribution of the characteristic points of the target fingerprint area image;
s203, performing circular image interception on the target fingerprint area image according to M different circle centers to obtain M circular fingerprint area images, wherein M is an integer larger than 3;
s204, selecting a target circular fingerprint area image from the M circular fingerprint area images, wherein the number of characteristic points contained in the target circular fingerprint area image is larger than that of other circular fingerprint area images in the M circular fingerprint area images;
s205, dividing the target circular fingerprint area image to obtain N circular rings, wherein the widths of the N circular rings are the same;
s206, starting from the circular ring with the minimum radius in the N circular rings, sequentially matching the N circular rings with the preset fingerprint template for feature points, and accumulating the matching values of the matched circular rings;
and S207, immediately stopping the characteristic point matching when the accumulated matching value is larger than a preset matching threshold value, and outputting a successful matching result.
Wherein, the electronic device can perform image segmentation on the first layer fingerprint image to obtain a target fingerprint area image, further analyze the feature point distribution of the target fingerprint area image, perform circular image interception on the target fingerprint area image according to M different circle centers to obtain M circular fingerprint area images, M is an integer greater than 3, select the target circular fingerprint area image from the M circular fingerprint area images, the number of the feature points contained in the target circular fingerprint area image is greater than that of other circular fingerprint area images in the M circular fingerprint area images, divide the target circular fingerprint area image to obtain N circular rings, the ring widths of the N circular rings are the same, perform feature point matching on the N circular rings with a preset fingerprint template in sequence from the circular ring with the smallest radius among the N circular rings, and accumulate the matching values of the matched circular rings, thus, in the fingerprint identification process, the characteristic points of different positions or different fingerprints can be used for matching, namely, the whole fingerprint image is sampled, and the sampling can cover the whole fingerprint area, so that corresponding standard reaching characteristics can be found from each area for matching, when the accumulated matching value is greater than a preset matching threshold value, the characteristic point matching is immediately stopped, and a prompt message indicating that the fingerprint identification is successful is output, so that the fingerprint identification can be quickly and accurately identified.
Optionally, the specific implementation manner of the noise identification operation may further include:
and performing convolution operation on the current layer fingerprint image data and a preset convolution kernel to obtain a convolution result matrix, obtaining the number e of elements with the element values lower than an element threshold value in the convolution result matrix, and obtaining the area of the noise data according to the number e.
There are various ways to obtain the noise data area according to the number E, for example, in an alternative embodiment, the noise data area corresponding to E can be determined from the interval-area mapping relationship according to the first interval where E is located. Of course, in an alternative embodiment, the area of the noise data may be obtained according to e and a predetermined function. F (e) ═ k × e + a, where k is a set coefficient and a is an adjustment amount.
As shown in fig. 3, fig. 3 is a diagram of an electronic device provided by the present application, and as shown in fig. 3, the electronic device includes: a processing circuit 301 and an ultrasonic fingerprint recognition module 302, wherein,
the processing circuit 301 is configured to start the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the ultrasonic fingerprint identification module 302 is used for collecting at least one layer of fingerprint picture data of a target object;
the processing circuit 301 is configured to match the at least one layer of fingerprint image data with at least one layer of fingerprint image data of a preset module to determine a matching result, determine that fingerprint verification is successful when the matching result is determined to be matching, and execute an operation corresponding to the successful fingerprint verification.
The technical scheme that this application provided is when receiving the fingerprint and treating the instruction of gathering, gathers at least one deck fingerprint picture data through ultrasonic fingerprint identification module, and when confirming that fingerprint verification passes, execution and this fingerprint verification succeed in the operation that corresponds. According to the technical scheme, only at least one layer of fingerprint picture data is matched and collected, after the matching is successful, the fingerprint pictures after at least one layer of fingerprint pictures can not be collected and matched, the times of fingerprint collection and the calculated amount of matching are reduced, and the speed of fingerprint unlocking is improved, so that the fingerprint identification method has the advantages of being high in fingerprint identification speed and improving user experience.
In an optional scheme, if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit 301 is specifically configured to:
and performing quality evaluation on the multilayer fingerprint image data to obtain a plurality of image quality evaluation values, selecting an ith layer fingerprint image with the best quality evaluation from the plurality of image instruction evaluation values, and matching the ith layer fingerprint image with an ith layer fingerprint image of a preset fingerprint module to obtain a matching result.
In an optional scheme, if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit 301 may be specifically configured to:
the multilayer fingerprint image data and the multilayer fingerprint image data of the preset module are compared one by one, and the one by one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if the upper-layer fingerprint picture data of the multilayer fingerprint picture data are matched with the upper-layer fingerprint picture data of the preset module, ending the one-by-one comparison process, if the upper-layer fingerprint picture data are not matched with the preset module, continuing to perform comparison of the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched.
In an optional scheme, if the preliminary fingerprint picture is a multi-finger fingerprint picture, the processing circuit 301 may be specifically configured to:
and identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result.
In an optional scheme, if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit 301 may be specifically configured to:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data;
the noise identification operation specifically includes: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the total area of the beta set intervals is the area of noise data.
Referring to fig. 4A, fig. 4A provides a fingerprint identification apparatus, which is applied to an electronic device, where the electronic device includes an ultrasonic fingerprint identification module; the device comprises: an obtaining unit 401, a matching unit 402, an executing unit 403, wherein,
the acquisition unit 401 is configured to acquire at least one layer of fingerprint image data of a target object through the ultrasonic fingerprint identification module when a fingerprint to-be-acquired instruction is received;
a matching unit 402, configured to match the at least one layer of fingerprint image data with at least one layer of fingerprint image data of a preset module to determine a matching result;
an executing unit 403, configured to determine that the fingerprint verification is successful and execute an operation corresponding to the successful fingerprint verification when it is determined that the matching result is matching.
The technical scheme that this application provided is when receiving the fingerprint and treating the instruction of gathering, gathers at least one deck fingerprint picture data through ultrasonic fingerprint identification module, and when confirming that fingerprint verification passes, execution and this fingerprint verification succeed in the operation that corresponds. According to the technical scheme, only at least one layer of fingerprint picture data is matched and collected, after the matching is successful, the fingerprint pictures after at least one layer of fingerprint pictures can not be collected and matched, the times of fingerprint collection and the calculated amount of matching are reduced, and the speed of fingerprint unlocking is improved, so that the fingerprint identification method has the advantages of being high in fingerprint identification speed and improving user experience.
Referring to fig. 4B, in an alternative, if the preliminary fingerprint picture is a multi-finger fingerprint picture, the matching unit 402 may specifically include:
the quality evaluation module 4021 is configured to perform quality evaluation on the multi-layer fingerprint image data to obtain a plurality of image quality evaluation values;
the comparison module 4022 is configured to select an ith layer of fingerprint image with the best quality evaluation from the multiple image instruction evaluation values, and match the ith layer of fingerprint image with an ith layer of fingerprint image of a preset fingerprint module to obtain a matching result.
If the preliminary fingerprint picture is a multi-fingerprint picture, the matching unit 402 may be specifically configured to:
the multilayer fingerprint image data and the multilayer fingerprint image data of the preset module are compared one by one, and the one by one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if the upper-layer fingerprint picture data of the multilayer fingerprint picture data are matched with the upper-layer fingerprint picture data of the preset module, ending the one-by-one comparison process, if the upper-layer fingerprint picture data are not matched with the preset module, continuing to perform comparison of the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched.
If the at least one layer of fingerprint image data is a multi-layer fingerprint image, the matching unit 402 specifically includes:
and identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result.
It can be understood that the functions of each program module of the fingerprint identification device of this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (9)
1. An electronic device, comprising a processing circuit and an ultrasonic fingerprint identification module connected to the processing circuit, wherein,
the processing circuit is used for starting the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the ultrasonic fingerprint identification module is used for collecting at least one layer of fingerprint picture data of a target object;
the processing circuit is used for matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result, when the matching result is determined to be matched, determining that fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification;
if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit is specifically configured to: identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result;
wherein the processing circuit is specifically configured to:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data;
the noise identification operation specifically includes: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the total area of the beta set intervals is the area of noise data.
2. The electronic device according to claim 1, wherein if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit is specifically configured to:
and performing quality evaluation on the multilayer fingerprint image data to obtain a plurality of image quality evaluation values, selecting an ith layer fingerprint image with the best quality evaluation from the plurality of image quality evaluation values, and matching the ith layer fingerprint image with an ith layer fingerprint image of a preset fingerprint module to obtain a matching result.
3. The electronic device according to claim 1, wherein if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the processing circuit is specifically configured to:
the multilayer fingerprint image data and the multilayer fingerprint image data of the preset module are compared one by one, and the one by one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if the upper-layer fingerprint picture data of the multilayer fingerprint picture data are matched with the upper-layer fingerprint picture data of the preset module, ending the one-by-one comparison process, if the upper-layer fingerprint picture data are not matched with the preset module, continuing to perform comparison of the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched.
4. The fingerprint identification method is characterized by being applied to electronic equipment, wherein the electronic equipment comprises an ultrasonic fingerprint identification module; the method comprises the following steps:
when receiving a fingerprint to-be-acquired instruction, acquiring at least one layer of fingerprint picture data of a target object;
matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result;
when the matching result is determined to be matched, determining that the fingerprint verification is successful, and executing operation corresponding to the successful fingerprint verification;
if the at least one layer of fingerprint picture data is a multilayer fingerprint picture, matching the at least one layer of fingerprint picture data with the at least one layer of fingerprint picture data of the preset module to determine a matching result specifically comprises: identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result;
the noise data area determination method specifically includes:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data;
the noise identification operation specifically includes: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the total area of the beta set intervals is the area of noise data.
5. The method according to claim 4, wherein, if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the matching the at least one layer of fingerprint picture data with the at least one layer of fingerprint picture data of the preset module to determine the matching result specifically comprises:
and performing quality evaluation on the multilayer fingerprint image data to obtain a plurality of image quality evaluation values, selecting an ith layer fingerprint image with the best quality evaluation from the plurality of image quality evaluation values, and matching the ith layer fingerprint image with an ith layer fingerprint image of a preset fingerprint module to obtain a matching result.
6. The method according to claim 4, wherein, if the at least one layer of fingerprint picture data is a multi-layer fingerprint picture, the matching the at least one layer of fingerprint picture data with the at least one layer of fingerprint picture data of the preset module to determine the matching result specifically comprises:
the multilayer fingerprint image data and the multilayer fingerprint image data of the preset module are compared one by one, and the one by one comparison process specifically comprises the following steps: and matching the upper-layer fingerprint picture data of the multilayer fingerprint picture data with the upper-layer fingerprint picture data of the preset module, if the upper-layer fingerprint picture data of the multilayer fingerprint picture data are matched with the upper-layer fingerprint picture data of the preset module, ending the one-by-one comparison process, if the upper-layer fingerprint picture data are not matched with the preset module, continuing to perform comparison of the subsequent-layer fingerprint picture data of the upper-layer fingerprint picture data until the matching is successful or the multilayer fingerprint picture data are completely matched.
7. The fingerprint identification device is characterized by being applied to electronic equipment, wherein the electronic equipment comprises an ultrasonic fingerprint identification module; the device comprises: an acquisition unit, a matching unit, an execution unit, wherein,
the acquisition unit is used for acquiring at least one layer of fingerprint image data of a target object through the ultrasonic fingerprint identification module when receiving a fingerprint to-be-acquired instruction;
the matching unit is used for matching the at least one layer of fingerprint picture data with at least one layer of fingerprint picture data of a preset module to determine a matching result;
the execution unit is used for determining that the fingerprint verification is successful and executing the operation corresponding to the successful fingerprint verification when the matching result is determined to be matching;
if the at least one layer of fingerprint picture data is a multilayer fingerprint picture, matching the at least one layer of fingerprint picture data with the at least one layer of fingerprint picture data of the preset module to determine a matching result specifically comprises: identifying and determining a plurality of noise data areas corresponding to the multi-layer fingerprint picture data for each layer of fingerprint picture data in the multi-layer fingerprint picture data, selecting alpha-layer fingerprint picture data with the smallest noise data area from the plurality of noise data areas, and matching the alpha-layer fingerprint picture data with alpha-layer fingerprint picture data of a preset fingerprint module to obtain a matching result;
the noise data area determination method specifically includes:
performing noise identification operation on each layer of fingerprint picture data in the multilayer fingerprint picture data one by one to obtain the noise data area of each layer of fingerprint picture data;
the noise identification operation specifically includes: the method comprises the steps of carrying out feature point extraction operation on current layer fingerprint picture data to obtain a plurality of feature points and a distribution condition of the feature points, dividing the current layer fingerprint picture data into a plurality of set intervals, and obtaining beta set intervals which do not contain the feature points in the plurality of set intervals, wherein the total area of the beta set intervals is the area of noise data.
8. An electronic device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps in the method of any of claims 4-6.
9. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any of the claims 4-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910610655.3A CN110378263B (en) | 2019-07-08 | 2019-07-08 | Fingerprint identification method and related product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910610655.3A CN110378263B (en) | 2019-07-08 | 2019-07-08 | Fingerprint identification method and related product |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110378263A CN110378263A (en) | 2019-10-25 |
| CN110378263B true CN110378263B (en) | 2021-07-13 |
Family
ID=68252367
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910610655.3A Active CN110378263B (en) | 2019-07-08 | 2019-07-08 | Fingerprint identification method and related product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110378263B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111681551B (en) * | 2020-06-28 | 2021-07-06 | 武汉华星光电技术有限公司 | Display module and electronic equipment |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102136024A (en) * | 2010-01-27 | 2011-07-27 | 中国科学院自动化研究所 | Biometric feature identification performance assessment and diagnosis optimizing system |
| CN105117086A (en) * | 2015-09-11 | 2015-12-02 | 小米科技有限责任公司 | Fingerprint recognition system, fingerprint recognition realizing method and device and electronic equipment |
| CN105912915A (en) * | 2016-05-27 | 2016-08-31 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN105912920A (en) * | 2016-06-17 | 2016-08-31 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN106203023A (en) * | 2015-05-04 | 2016-12-07 | 小米科技有限责任公司 | A kind of terminal carrying out fingerprint recognition |
| CN106485195A (en) * | 2015-08-27 | 2017-03-08 | 瑞鼎科技股份有限公司 | Capacitance type fingerprint sensing device further and capacitance type fingerprint method for sensing |
| CN106503628A (en) * | 2016-09-30 | 2017-03-15 | 北京小米移动软件有限公司 | method and device for fingerprint matching |
| CN107103223A (en) * | 2017-04-28 | 2017-08-29 | 广东欧珀移动通信有限公司 | Solve lock control method and Related product |
| CN109376703A (en) * | 2018-11-30 | 2019-02-22 | Oppo广东移动通信有限公司 | Fingerprint identification method and Related product |
| CN109426766A (en) * | 2017-08-23 | 2019-03-05 | 上海箩箕技术有限公司 | Fingerprint imaging mould group and electronic equipment |
| CN109858227A (en) * | 2019-02-02 | 2019-06-07 | Oppo广东移动通信有限公司 | Fingerprint input method, device, electronic equipment and storage medium |
| CN109886162A (en) * | 2019-01-30 | 2019-06-14 | Oppo广东移动通信有限公司 | Fingerprint authentication method and relevant apparatus |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107784271B (en) * | 2017-09-27 | 2021-02-09 | Oppo广东移动通信有限公司 | Fingerprint identification method and related product |
| CN107832599A (en) * | 2017-11-16 | 2018-03-23 | 珠海市魅族科技有限公司 | A kind of terminal and unlocked by fingerprint method |
| CN108171178A (en) * | 2017-12-29 | 2018-06-15 | 昆山国显光电有限公司 | A kind of method for controlling fingerprint identification and touch panel, display device |
-
2019
- 2019-07-08 CN CN201910610655.3A patent/CN110378263B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102136024A (en) * | 2010-01-27 | 2011-07-27 | 中国科学院自动化研究所 | Biometric feature identification performance assessment and diagnosis optimizing system |
| CN106203023A (en) * | 2015-05-04 | 2016-12-07 | 小米科技有限责任公司 | A kind of terminal carrying out fingerprint recognition |
| CN106485195A (en) * | 2015-08-27 | 2017-03-08 | 瑞鼎科技股份有限公司 | Capacitance type fingerprint sensing device further and capacitance type fingerprint method for sensing |
| CN105117086A (en) * | 2015-09-11 | 2015-12-02 | 小米科技有限责任公司 | Fingerprint recognition system, fingerprint recognition realizing method and device and electronic equipment |
| CN105912915A (en) * | 2016-05-27 | 2016-08-31 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN105912920A (en) * | 2016-06-17 | 2016-08-31 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN106503628A (en) * | 2016-09-30 | 2017-03-15 | 北京小米移动软件有限公司 | method and device for fingerprint matching |
| CN107103223A (en) * | 2017-04-28 | 2017-08-29 | 广东欧珀移动通信有限公司 | Solve lock control method and Related product |
| CN109426766A (en) * | 2017-08-23 | 2019-03-05 | 上海箩箕技术有限公司 | Fingerprint imaging mould group and electronic equipment |
| CN109376703A (en) * | 2018-11-30 | 2019-02-22 | Oppo广东移动通信有限公司 | Fingerprint identification method and Related product |
| CN109886162A (en) * | 2019-01-30 | 2019-06-14 | Oppo广东移动通信有限公司 | Fingerprint authentication method and relevant apparatus |
| CN109858227A (en) * | 2019-02-02 | 2019-06-07 | Oppo广东移动通信有限公司 | Fingerprint input method, device, electronic equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| A Comparative Study of Fingerprint Image-Quality Estimation Methods;Fernando Alonso-Fernandez et al.;《IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY》;20071231;第2卷(第4期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110378263A (en) | 2019-10-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110286738B (en) | Fingerprint acquisition method and related product | |
| CN109241859B (en) | Fingerprint identification method and related product | |
| CN108701043B (en) | Display processing method and device | |
| CN109614865B (en) | Fingerprint identification method and related product | |
| CN110427741B (en) | Fingerprint identification method and related product | |
| CN110210395B (en) | Vein image acquisition method and related product | |
| CN110414410B (en) | Fingerprint acquisition method and related product | |
| CN109657561B (en) | Fingerprint acquisition method and related product | |
| CN109376700B (en) | Fingerprint identification method and related product | |
| CN110245607B (en) | Eyeball tracking method and related product | |
| CN110475020B (en) | Equipment control method and related product | |
| CN110276328B (en) | Fingerprint identification method and related product | |
| CN110298274B (en) | Optical fingerprint parameter upgrading method and related product | |
| CN110188666B (en) | Vein collection method and related products | |
| CN110263757B (en) | Fingerprint identification method and related product | |
| CN110263752B (en) | Fingerprint identification method and related product | |
| CN110221696B (en) | Eyeball tracking method and related product | |
| CN110378263B (en) | Fingerprint identification method and related product | |
| CN110210394B (en) | Vein image acquisition method and related product | |
| CN110188659B (en) | Health detection method and related product | |
| CN110796147B (en) | Image segmentation method and related product | |
| CN110244848B (en) | Reading control method and related equipment | |
| CN112989878A (en) | Pupil detection method and related product | |
| CN110399852B (en) | Control method of ultrasonic module and related product | |
| CN110276190B (en) | Fingerprint identification method and related product |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |