WO2017174010A1 - 一种指纹解锁的方法及终端 - Google Patents

一种指纹解锁的方法及终端 Download PDF

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Publication number
WO2017174010A1
WO2017174010A1 PCT/CN2017/079612 CN2017079612W WO2017174010A1 WO 2017174010 A1 WO2017174010 A1 WO 2017174010A1 CN 2017079612 W CN2017079612 W CN 2017079612W WO 2017174010 A1 WO2017174010 A1 WO 2017174010A1
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WIPO (PCT)
Prior art keywords
fingerprint
image
image quality
target
images
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PCT/CN2017/079612
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English (en)
French (fr)
Inventor
周意保
Original Assignee
广东欧珀移动通信有限公司
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 广东欧珀移动通信有限公司 filed Critical 广东欧珀移动通信有限公司
Priority to EP17778674.6A priority Critical patent/EP3401883B1/en
Publication of WO2017174010A1 publication Critical patent/WO2017174010A1/zh
Priority to US16/119,111 priority patent/US11188627B2/en
Priority to US16/197,078 priority patent/US10417406B2/en

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    • 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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
    • G06V10/993—Evaluation of the quality of the acquired pattern
    • 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
    • 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
    • G06V40/1376—Matching features related to ridge properties or fingerprint texture
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
    • G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/30—Individual registration on entry or exit not involving the use of a pass
    • G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
    • G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise

Definitions

  • the present invention relates to the field of terminal equipment technologies, and in particular, to a method and a terminal for unlocking a fingerprint.
  • Fingerprint recognition technology as a standard technology on the terminal, fingerprint recognition technology can be widely used not only for terminal unlocking, wake-up, mobile payment, and the like. While the fingerprint recognition technology is popular, in order to achieve fast unlocking, the unlocking time of the terminal is also a direct concern of the terminal manufacturer.
  • the embodiment of the invention provides a method and a terminal for unlocking a fingerprint, which can improve the efficiency of fingerprint unlocking.
  • a first aspect of the embodiments of the present invention provides a method for unlocking a fingerprint, including:
  • the terminal is unlocked.
  • a second aspect of the embodiments of the present invention provides a terminal, including:
  • the collecting unit is configured to collect fingerprints by adjusting adjustment parameters of the fingerprint collecting chip in the fingerprint identifying module when detecting that the fingerprint identifying module is pressed, to obtain a plurality of fingerprint images;
  • a determining unit configured to determine a target fingerprint image with the best image quality among the plurality of fingerprint images collected by the collecting unit
  • the unlocking unit is configured to unlock the terminal when the target fingerprint image determined by the determining unit and the preset fingerprint image are successfully matched.
  • a third aspect of the embodiments of the present invention provides a terminal, including:
  • a processor coupled to the memory
  • the processor invokes the executable program code stored in the memory to perform some or all of the steps as described in any of the first aspects of the embodiments of the present invention.
  • a fourth aspect of the embodiments of the present invention provides a computer storage medium for storing software instructions for a terminal as described in the third aspect, the software instructions being included for performing the description as described in the first aspect
  • the fingerprint is unlocked by the method designed by the program.
  • the fingerprint is collected by adjusting the adjustment parameters of the fingerprint collection chip in the fingerprint recognition module to obtain multiple fingerprint images, and the image quality in the plurality of fingerprint images is determined.
  • the best target fingerprint image and when the target fingerprint image and the preset fingerprint image match successfully, the terminal is unlocked. Therefore, the target fingerprint image with the best quality can be obtained by adjusting the adjustment parameter. Therefore, when the target fingerprint image is matched with the preset fingerprint image, the matching success rate between the two can be improved, that is, the efficiency of fingerprint unlocking is improved.
  • FIG. 1 is a schematic flow chart of a first embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart diagram of a second embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention
  • FIG. 3 is a schematic flowchart diagram of a third embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention
  • FIG. 4a is a schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present invention.
  • FIG. 4b is still another schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present disclosure.
  • FIG. 5 is a schematic structural diagram of a second embodiment of a terminal according to an embodiment of the present invention.
  • the embodiment of the invention provides a method and a terminal for unlocking a fingerprint, which can improve the efficiency of fingerprint unlocking.
  • references to "an embodiment” herein mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the invention.
  • the appearances of the phrases in various places in the specification are not necessarily referring to the same embodiments, and are not exclusive or alternative embodiments that are mutually exclusive. Those skilled in the art will understand and implicitly understand that the embodiments described herein can be combined with other embodiments.
  • the terminal described in the embodiment of the present invention may include a smart phone (such as an Android mobile phone, an iOS mobile phone, a Windows Phone mobile phone, etc.), a tablet computer, a palmtop computer, a notebook computer, a mobile Internet device (MID, Mobile Internet Devices), or a wearable device.
  • a smart phone such as an Android mobile phone, an iOS mobile phone, a Windows Phone mobile phone, etc.
  • a tablet computer such as an Android mobile phone, an iOS mobile phone, a Windows Phone mobile phone, etc.
  • a palmtop computer such as a notebook computer
  • MID Mobile Internet Devices
  • FIG. 1 is a schematic flowchart diagram of a first embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention.
  • the method for unlocking a fingerprint described in this embodiment includes the following steps:
  • the fingerprint recognition module when the terminal detects that the fingerprint recognition module is pressed, can collect the fingerprint image of the process of pressing the fingerprint recognition module by the user, and adjust the adjustment parameter of the fingerprint recognition chip of the fingerprint recognition module. Fingerprints are collected, and multiple fingerprint images can be obtained under different adjustment parameters.
  • the adjustment parameters of the fingerprint recognition chip in the fingerprint recognition module mainly include a digital-to-analog conversion offset (adc shift) and an analog-to-digital conversion increment (adc gain).
  • Adc shift is used to indicate the offset of the digital-to-analog converter.
  • the fingerprint acquisition chip can collect 56*172 pixels. Each pixel corresponds to a pixel value in the process of fingerprint acquisition. , you will get 10752 pixel values, in which, after normalizing the pixel values (that is, the pixel values are concentrated between 0 and 1), most of the pixel values will be distributed between 0.4 and 0.8. Since the pixel values of each pixel are different, a pixel dot map can be formed. Adc shift can have several gear positions.
  • Adc gain is used to represent the gain of the exponential mode converter. The larger the gain, the more dispersed the distribution map. The smaller the gain, the more concentrated the distribution map. If the distribution map is more dispersed, the contrast of the image will be higher. The darker the blacker pixels, the whiter the whiter pixels in the fingerprint image.
  • the adjustment parameters of the fingerprint recognition chip in the fingerprint identification module may further include: pixel gain, pixel gain, which is used to represent the gain of the pixel, and pixel gain is determined by the capacitance of the amplifier in parallel, and the amplifier has a plurality of capacitors in parallel, each capacitor Both can be controlled by one switch. The more the switch is closed, the larger the gain, the larger the pixel value, and the stronger the signal strength. In practical applications, pixel gain is usually fixed during the control of adc. Mainly by adjusting the adjustment parameters adc shift and adc gain, where adc shift is used to adjust the position of the entire map, adc gain is the concentration and dispersion of the map.
  • the captured image can be debugged through different adjustment parameters. If there are 5 gears in each of the adc shift and the adc gain, then there are 25 combinations, and up to 25 can be collected at a time. Fingerprint image.
  • the adjustment parameter includes at least a digital-to-analog conversion offset and a digital-to-analog conversion increment, wherein the digital-to-analog conversion offset includes M first adjustment gears, and the digital-to-analog conversion increment includes N Second, adjust the gear position, wherein M and N are integers greater than 1, then, the fingerprint recognition mode is detected at the terminal When the group is pressed, the fingerprint is collected by using any one of the first adjustment gear positions and any one of the N second adjustment gear positions selected from the M first adjustment gear positions to obtain a plurality of Fingerprint images. Preferably, three fingerprint images are obtained.
  • three fingerprint images are obtained by adjusting adc shift and adc gain, respectively, a first fingerprint image, a second fingerprint image, and a third fingerprint image, that is, adc shift and adc gain, respectively. Adjust to the highest level, get the first fingerprint image; adjust the adc shift and adc gain to the lowest file to get the second fingerprint image; adjust the adc shift and adc gain to the middle file to get the third fingerprint image.
  • the terminal may select a target fingerprint image with the best image quality from the plurality of fingerprint images.
  • the terminal may perform image quality evaluation on each of the plurality of fingerprint images according to one or more image quality evaluation indicators to obtain a plurality of image quality evaluation values, and select a fingerprint image corresponding to the largest image quality evaluation value as the target fingerprint.
  • image quality evaluation indicators may include, but are not limited to, image definition, signal to noise ratio, texture definition, fingerprint image coverage, contrast, average gray scale, and the like.
  • the terminal may perform image quality evaluation on each of the plurality of fingerprint images according to the same image quality evaluation index to obtain a plurality of image quality evaluation values, and select a fingerprint image corresponding to the largest image quality evaluation value as the target fingerprint. image.
  • the terminal may separately acquire the sharpness of the plurality of fingerprint images, and select the fingerprint image with the highest image sharpness as the target fingerprint image.
  • the terminal may separately acquire the signal to noise ratio of the plurality of fingerprint images, and select the fingerprint image with the highest signal to noise ratio as the target fingerprint image.
  • the terminal may separately acquire fingerprint image coverage of the plurality of fingerprint images, and select the fingerprint image with the highest coverage of the fingerprint image as the target fingerprint image.
  • the terminal may separately acquire the texture definition of the fingerprint image of the plurality of fingerprint images, and select the fingerprint image with the highest texture definition as the target fingerprint image.
  • the terminal may separately acquire fingerprint image coverage of the plurality of fingerprint images, and select the fingerprint image with the highest coverage of the fingerprint image as the target fingerprint image.
  • the terminal may perform image quality evaluation on each of the plurality of fingerprint images according to at least two image quality evaluation indicators to obtain a plurality of image quality evaluation values, and select the largest one.
  • the fingerprint image corresponding to the image quality evaluation is taken as the target fingerprint image. That is, the target fingerprint image with the best image quality among the plurality of fingerprint images is determined by using at least two image quality evaluation indexes for evaluating the fingerprint image.
  • the quality evaluation value of each of the plurality of fingerprint images is calculated by using the following formula, and the fingerprint image corresponding to the maximum value of the plurality of quality evaluation values is used as the target fingerprint image with the best image quality, wherein
  • the formula is as follows:
  • S represents a quality evaluation value
  • K represents the number of image quality evaluation indicators
  • P i represents an evaluation value of the i-th image quality evaluation index.
  • a weight indicating an i-th image quality evaluation index, wherein Where K is an integer greater than one.
  • the terminal when the target fingerprint image and the preset fingerprint image are successfully matched, the terminal may unlock the terminal.
  • the matching value between the target fingerprint image and the preset fingerprint image may be determined. If the matching value reaches a certain threshold, the matching may be considered successful, and if the matching value does not reach the For a certain threshold, the fingerprint feature may be considered to not match the preset fingerprint feature.
  • the fingerprint texture of the target fingerprint image may be matched with the fingerprint texture of the preset fingerprint image. If the matching value reaches a certain threshold, the fingerprint texture of the target fingerprint image may be considered as The fingerprint pattern of the preset fingerprint image is successfully matched. If the matching value does not reach the certain threshold, the fingerprint pattern of the target fingerprint image may not be matched with the fingerprint pattern of the preset fingerprint image.
  • the feature points of the target fingerprint image such as Harris corner points and Scale-invariant feature transform (SIFT) corner points
  • SIFT Scale-invariant feature transform
  • the fingerprint is collected by adjusting the adjustment parameters of the fingerprint collection chip in the fingerprint recognition module to obtain multiple fingerprint images, and the image quality in the plurality of fingerprint images is determined.
  • the best target fingerprint image and when the target fingerprint image and the preset fingerprint image match successfully, the terminal is unlocked. Therefore, the target fingerprint image with the best quality can be obtained by adjusting the adjustment parameter. Therefore, when the target fingerprint image is matched with the preset fingerprint image, the matching success rate between the two can be improved, that is, the efficiency of fingerprint unlocking is improved.
  • the fingerprint of the finger of the user is the fingerprint of the dry finger or the fingerprint of the wet finger
  • the number of times the user presses the fingerprint recognition module can be reduced, thereby improving the efficiency of fingerprint unlocking and reducing the time for fingerprint unlocking.
  • FIG. 2 is a schematic flowchart diagram of a second embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention.
  • the method for unlocking a fingerprint described in this embodiment includes the following steps:
  • 201 When detecting that the fingerprint recognition module is pressed, determining whether the fingerprint pressed by the fingerprint recognition module is a fingerprint of a dry finger or a fingerprint of a wet finger.
  • the terminal when the terminal detects that the fingerprint recognition module is pressed, it may be determined that the fingerprint of the fingerprint recognition module is from a dry finger or a wet finger, because the fingerprint pattern in the fingerprint image of the dry finger is intermittent.
  • the fingerprint image of the fingerprint image of the wet finger is blurred in a large area of the fingerprint, and the fingerprint texture is almost indistinguishable. Therefore, by analyzing the fingerprint image, it is determined whether the fingerprint image is from a dry finger or a wet finger.
  • the terminal may determine whether the fingerprint is from a dry finger or a wet finger by extracting a texture feature of the fingerprint of the fingerprint recognition module. If the texture of the fingerprint image is intermittent, the fingerprint image belongs to a dry finger. If a fingerprint area of a large area is blurred in the fingerprint image, the fingerprint image belongs to a wet finger.
  • the terminal may determine that the number of feature points of the fingerprint of the fingerprint recognition module is pressed, and the number of the feature points is determined to be in a preset range.
  • the preset range may be smaller than the first threshold.
  • the first threshold may be a certain percentage of the number of feature points of the preset fingerprint image, for example, 50%, or the first threshold is a default of the system. value.
  • the preset range may be between the second threshold and the third threshold, wherein the second threshold is smaller than the third threshold, and the third threshold may be a certain percentage of the number of feature points of the preset fingerprint image, for example , 50%, or, the third threshold is a certain value of the system default, and the second threshold may be a certain percentage of the number of feature points of the preset fingerprint image, for example, 30%, or the second threshold is the default of the system. A value. Under normal circumstances, the characteristics of dry fingers or wet fingers If the number of feature points is less than the first threshold, the fingerprint is from a dry finger or a wet finger.
  • the terminal may directly collect the fingerprint by using the default adjustment parameter to obtain the fingerprint image.
  • the fingerprint image is matched with the preset fingerprint image, and when the matching is successful, the terminal is unlocked.
  • step 202-step 204 described in FIG. 2 may refer to step 101-step 103 described in FIG.
  • the fingerprint is collected by adjusting the adjustment parameter of the fingerprint acquisition chip in the fingerprint recognition module.
  • the target fingerprint image with the best quality can be obtained by adjusting the adjustment parameter. Therefore, when the target fingerprint image is matched with the preset fingerprint image, the matching success rate between the two can be improved, that is, the efficiency of fingerprint unlocking is improved.
  • the fingerprint of the finger of the user is the fingerprint of the dry finger or the fingerprint of the wet finger
  • the number of times the user presses the fingerprint recognition module can be reduced, thereby improving the efficiency of fingerprint unlocking and reducing the time for fingerprint unlocking.
  • FIG. 3 is a schematic flowchart diagram of a third embodiment of a method for unlocking a fingerprint according to an embodiment of the present invention.
  • the method for unlocking a fingerprint described in this embodiment includes the following steps:
  • the fingerprint recognition module 301 When detecting that the fingerprint recognition module is pressed, determine whether the fingerprint pressed by the fingerprint recognition module is a fingerprint of a dry finger or a fingerprint of a wet finger.
  • step 301 described in FIG. 3 may refer to step 201 described in FIG. 2, and step 302-step 304 described in FIG. 3 may refer to step 101-step 103 described in FIG.
  • the fingerprint is collected by adjusting the adjustment parameter of the fingerprint acquisition chip in the fingerprint recognition module.
  • the target fingerprint image with the best quality can be obtained by adjusting the adjustment parameter. Therefore, when the target fingerprint image is matched with the preset fingerprint image, the matching success rate between the two can be improved, that is, the efficiency of fingerprint unlocking is improved.
  • the fingerprint of the finger of the user is the fingerprint of the dry finger or the fingerprint of the wet finger
  • the number of times the user presses the fingerprint recognition module can be reduced, thereby improving the efficiency of fingerprint unlocking and reducing the time for fingerprint unlocking.
  • FIG. 4 is a schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present invention.
  • the terminal 400 described in this embodiment includes an acquisition unit 401, a determination unit 402, and an unlocking unit 403.
  • the collecting unit 401 is configured to: when detecting that the fingerprint recognition module is pressed, acquiring a fingerprint by adjusting an adjustment parameter of the fingerprint collection chip in the fingerprint identification module to obtain a plurality of fingerprint images;
  • a determining unit 402 configured to determine a target fingerprint image with the best image quality among the plurality of fingerprint images collected by the collecting unit 401;
  • the unlocking unit 403 is configured to unlock the terminal when the target fingerprint image determined by the determining unit 402 matches the preset fingerprint image.
  • the adjustment parameter includes at least a digital-to-analog conversion offset and a digital-to-analog conversion increment, wherein the digital-to-analog conversion offset includes M first adjustment gear positions, and the digital-to-analog conversion increment includes N second adjustment gear positions, wherein the M and the N are integers greater than 1;
  • the collecting unit 401 collects fingerprints by adjusting the adjustment parameters of the fingerprint collection chip in the fingerprint identification module to obtain a plurality of fingerprint images, which specifically includes:
  • the determining unit 402 determines the target fingerprint image with the best image quality among the plurality of fingerprint images collected by the collecting unit 401, and specifically includes:
  • a target fingerprint image having the best image quality among the plurality of fingerprint images is determined using at least one image quality evaluation index for evaluating the fingerprint image.
  • the determining unit 402 determines the target fingerprint image with the best image quality among the plurality of fingerprint images collected by the collecting unit 401, and further includes:
  • the image quality evaluation value of each of the plurality of fingerprint images is calculated by using the following formula, and the fingerprint image corresponding to the maximum value of the image quality evaluation values is used as the target fingerprint image with the best image quality, wherein , the formula is as follows:
  • the S represents the quality evaluation value
  • the K represents the number of the image quality evaluation indicators
  • the P i represents an image quality evaluation value of the i-th image quality evaluation index, Representing the weight of the i-th image quality evaluation index, wherein
  • the terminal described in FIG. 4a may further include:
  • the determining unit 404 is configured to determine, when the fingerprint recognition module is pressed, whether the fingerprint of the fingerprint recognition module is a fingerprint of a dry finger or a fingerprint of a wet finger, and the determination result of the determining unit 404 is When yes, the collection unit 401 collects fingerprints by adjusting adjustment parameters of the fingerprint collection chip in the fingerprint recognition module to obtain a plurality of fingerprint images.
  • the determining unit 401 is specifically configured to:
  • Determining whether the fingerprint is from a dry finger or a wet finger by extracting a texture feature of the fingerprint pressing the fingerprint recognition module;
  • the terminal described in the embodiment of the present invention can collect fingerprints by adjusting adjustment parameters of the fingerprint collection chip in the fingerprint identification module when detecting that the fingerprint recognition module is pressed, to obtain multiple fingerprints. For example, the target fingerprint image with the best image quality in the plurality of fingerprint images is determined, and when the target fingerprint image and the preset fingerprint image are successfully matched, the terminal is unlocked. Therefore, the target fingerprint image with the best quality can be obtained by adjusting the adjustment parameter. Therefore, when the target fingerprint image is matched with the preset fingerprint image, the matching success rate between the two can be improved, that is, the efficiency of fingerprint unlocking is improved. In particular, when the fingerprint of the finger of the user is the fingerprint of the dry finger or the fingerprint of the wet finger, the number of times the user presses the fingerprint recognition module can be reduced, thereby improving the efficiency of fingerprint unlocking and reducing the time for fingerprint unlocking.
  • FIG. 5 is a schematic structural diagram of a second embodiment of a terminal according to an embodiment of the present invention.
  • the terminal 500 described in this embodiment includes: at least one input device 1000; at least one output device 2000; at least one processor 3000, such as a CPU; and a memory 4000, the input device 1000, the output device 2000, the processor 3000, and The memory 4000 is connected by a bus 5000.
  • the input device 1000 may specifically be a touch panel, a physical button, a keyboard, a mouse, or a fingerprint recognition module.
  • the output device 2000 described above may specifically be a display screen.
  • the above memory 4000 may be a high speed RAM memory or a non-volatile memory such as a disk memory.
  • the above memory 4000 is used to store a set of program codes, and the input device 1000, the output device 2000, and the processor 3000 are used to call the program code stored in the memory 4000, and perform the following operations:
  • the processor 3000 is configured to:
  • the terminal is unlocked.
  • the adjustment parameter includes at least a digital-to-analog conversion offset and a digital-to-analog conversion increment, wherein the digital-to-analog conversion offset includes M first adjustment gear positions, and the digital-to-analog conversion increment includes N second adjustment gear positions, wherein the M and the N are integers greater than 1;
  • the processor 3000 collects fingerprints by adjusting adjustment parameters of the fingerprint collection chip in the fingerprint identification module to obtain multiple fingerprint images, including:
  • the processor 3000 determines a target fingerprint image with the best image quality among the plurality of fingerprint images, including:
  • a target fingerprint image having the best image quality among the plurality of fingerprint images is determined using at least one image quality evaluation index for evaluating the fingerprint image.
  • the processor 3000 determines, by using at least one image quality evaluation indicator for evaluating the fingerprint image, a target fingerprint image with the best image quality among the plurality of fingerprint images, including:
  • the image quality evaluation value of each of the plurality of fingerprint images is calculated by using the following formula, and the fingerprint image corresponding to the maximum value of the image quality evaluation values is used as the target fingerprint image with the best image quality, wherein , the formula is as follows:
  • the S represents the quality evaluation value
  • the K represents the number of the image quality evaluation indicators
  • the P i represents an image quality evaluation value of the i-th image quality evaluation index, Representing the weight of the i-th image quality evaluation index, wherein
  • the processor 3000 when detecting that the fingerprint identification module is pressed, is further configured to:
  • Determining whether the fingerprint of the fingerprint recognition module is a fingerprint of a dry finger or a fingerprint of a wet finger, and if so, performing the adjustment of the fingerprint of the fingerprint acquisition chip in the fingerprint identification module to acquire a fingerprint, so as to obtain a plurality of fingerprints The steps of a fingerprint image.
  • the processor 3000 determines whether the fingerprint of the fingerprint recognition module is a fingerprint of a dry finger or a fingerprint of a wet finger, including:
  • Determining whether the fingerprint is from a dry finger or a wet finger by extracting a texture feature of the fingerprint pressing the fingerprint recognition module;
  • the input device 1000, the output device 2000, and the processor 3000 described in the embodiments of the present invention may perform the first embodiment, the second embodiment, and the third method of the fingerprint unlocking method provided by the embodiment of the present invention.
  • the implementation manners in the embodiments may also be implemented in the first embodiment, the second embodiment, and the third embodiment of the terminal provided by the embodiment of the present invention, and details are not described herein again. .
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium can store a program, and the program includes some or all of the steps of the method for unlocking the fingerprint according to any one of the foregoing method embodiments.
  • the disclosed apparatus may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical or otherwise.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in various embodiments of the present invention may be integrated in one processing unit. It is also possible that each unit physically exists alone, or two or more units may be integrated in one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • the technical solution of the present invention which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and the like. .

Abstract

一种指纹解锁的方法及一种终端，所述方法包括：在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；确定所述多个指纹图像中图像质量最好的目标指纹图像；在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配成功时，对终端进行解锁，该过程中可提高两者之间的匹配成功率，因而，可提高指纹解锁的效率。

Description

一种指纹解锁的方法及终端 技术领域
本发明涉及终端设备技术领域，具体涉及一种指纹解锁的方法及终端。
背景技术
随着信息技术的快速发展，终端(如手机、平板电脑等等)的使用越来越普及。指纹识别技术作为终端上的标配技术，指纹识别技术不仅可以用于终端的解锁、唤醒、移动支付等等中得到广泛应用。在指纹识别技术流行的同时，为了实现快速解锁，终端的解锁时间也是终端制造商直接关心的问题。
实际应用中，用户时常会发现，在手指过干或者过湿时，需要多次按压指纹识别模组，才有可能解锁成功，因而，降低了指纹解锁效率。
发明内容
本发明实施例提供了一种指纹解锁的方法及终端，可以提升指纹解锁的效率。
本发明实施例第一方面提供了一种指纹解锁的方法，包括：
在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
确定所述多个指纹图像中图像质量最好的目标指纹图像；
在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
本发明实施例第二方面提供了一种终端，包括：
采集单元，用于在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
确定单元，用于确定所述采集单元采集的所述多个指纹图像中图像质量最好的目标指纹图像；
解锁单元，用于在所述确定单元确定的所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
本发明实施例第三方面提供了一种终端，包括：
存储有可执行程序代码的存储器；
与所述存储器耦合的处理器；
所述处理器调用所述存储器中存储的所述可执行程序代码，执行如本发明实施例第一方面任一方法中所描述的部分或全部步骤。
本发明实施例第四方面提供了一种计算机存储介质，所述计算机存储介质用于存储如第三方面所描述的终端所用的软件指令，所述软件指令包含用于执行如第一方面所描述的指纹解锁的方法所设计的程序。
实施本发明实施例，具有如下有益效果：
通过本发明实施例在检测到指纹识别模组被按压时，通过调节指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，确定出该多个指纹图像中图像质量最好的目标指纹图像，并在目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。从而，可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配时，可提高两者之间的匹配成功率，即提高指纹解锁的效率。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例提供的一种指纹解锁的方法的第一实施例流程示意图；
图2是本发明实施例提供的一种指纹解锁的方法的第二实施例流程示意图；
图3是本发明实施例提供的一种指纹解锁的方法的第三实施例流程示意图；
图4a是本发明实施例提供的一种终端的第一实施例结构示意图；
图4b是本发明实施例提供的一种终端的第一实施例又一结构示意图；
图5是本发明实施例提供的一种终端的第二实施例结构示意图。
具体实施方式
本发明实施例提供了一种指纹解锁的方法及终端，可以提升指纹解锁的效率。
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
本发明的说明书和权利要求书及所述附图中的术语“第一”、“第二”、“第三”和“第四”等是用于区别不同对象，而不是用于描述特定顺序。此外，术语“包括”和“具有”以及它们任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本发明的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
本发明实施例所描述的终端可以包括智能手机(如Android手机、iOS手机、Windows Phone手机等)、平板电脑、掌上电脑、笔记本电脑、移动互联网设备(MID，Mobile Internet Devices)或穿戴式设备等，上述终端仅是举例，而非穷举，包含但不限于上述终端。
请参阅图1，为本发明实施例提供的一种指纹解锁的方法的第一实施例流程示意图。本实施例中所描述的指纹解锁的方法，包括以下步骤：
101：在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像。
本发明实施例中，在终端检测到指纹识别模组被按压时，指纹识别模组可采集用户在按压指纹识别模组的过程的指纹图像，通过调节指纹识别模组的指纹识别芯片的调节参数采集指纹，在不同的调节参数下，可得到多个指纹图像。
具体地，指纹识别模组中指纹识别芯片的调节参数主要包括数模转换偏移量(adc shift)和数模转换增量(adc gain)。adc shift用于表示数模转换器的偏移量，例如，指纹采集芯片可采集56*172个像素点，其中，每个像素点在指纹采集芯片采图的过程中都对应一个像素值，那么，便会得到10752个像素值，其中，在将像素值归一化(即像素值集中在0～1之间)后，通常情况下，大部分像素值的大小会分布在0.4-0.8之间，由于每个像素点的像素值不同，因而，可形成一个像素点分布图。adc shift可有几个档位，若adc shift值越高，像素点的分布图对应的整体像素值就越大，指纹图像就会表现得越黑。adc gain用于表示指数模转化器的增益，增益越大，分布图会越分散，增益越小，分布图会越集中，若分布图越分散，则图像的对比度就越高，指纹图像中原本较黑的像素点越黑，指纹图像中原本较白的像素点越白。指纹识别模组中指纹识别芯片的调节参数还可包括：像素点增益pixel gain，pixel gain用于表示像素点的增益，pixel gain由放大器并联的电容决定的，放大器并联多个电容，每个电容均都可由一个开关进行控制，开关闭合得越多，增益越大，像素值越大，信号强度越强。在实际应用中，adc的控制过程中，pixel gain通常情况下是固定的。主要通过调节调节参数adc shift和adc gain，其中，adc shift用于调整整个分布图的位置，adc gain是调分布图的集中和分散情况。例如，利用用户在按压指纹识别模组时，可通过不同的调节参数来调试采集图像，假如adc shift和adc gain各有5个档位，那么就有25个组合，每次最多可采集25个指纹图像。
进一步可选地，调节参数至少包括数模转换偏移量和数模转换增量，其中，该数模转换偏移量包含M个第一调节档位，该数模转换增量包含N个第二调节档位，其中，M和N均为大于1的整数，那么，在终端检测到指纹识别模 组被按压时，通过多次从M个第一调节档位中的选取的任一第一调节档位和N个第二调节档位中的任一第二调节档位采集指纹，以得到多个指纹图像。优选地，可得到3个指纹图像，例如，通过调节将adc shift和adc gain得到3个指纹图像，分别为第一指纹图像、第二指纹图像和第三指纹图像，即将adc shift和adc gain均调到最高档，得到第一指纹图像；将adc shift和adc gain均调到最低档，得到第二指纹图像；将adc shift和adc gain均调到中间档，得到第三指纹图像。
102：确定所述多个指纹图像中图像质量最好的目标指纹图像。
本发明实施例中，终端可从多个指纹图像中选择图像质量最好的目标指纹图像。终端可按照一个或者多个图像质量评价指标对多个指纹图像中的每一指纹图像进行图像质量评价，以得到多个图像质量评价值，选择最大的图像质量评价值对应的指纹图像作为目标指纹图像。其中，图像质量评价指标可包括但不仅限于：图像清晰度、信噪比、纹路清晰度、指纹图像覆盖率、对比度、平均灰度等等。
一方面，终端可按照同一图像质量评价指标对多个指纹图像中的每一指纹图像进行图像质量评价，以得到多个图像质量评价值，选择最大的图像质量评价值对应的指纹图像作为目标指纹图像。
进一步可选地，终端可分别获取多个指纹图像的清晰度，选择图像清晰度最高的指纹图像作为目标指纹图像。
进一步可选地，终端可分别获取多个指纹图像的信噪比，选择信噪比最高的指纹图像作为目标指纹图像。
进一步可选地，终端可分别获取多个指纹图像的指纹图像覆盖率，选择指纹图像覆盖率最高的指纹图像作为目标指纹图像。
进一步可选地，终端可分别获取多个指纹图像的指纹图像的纹路清晰度，选择纹路清晰度最高的指纹图像作为目标指纹图像。
进一步可选地，终端可分别获取多个指纹图像的指纹图像覆盖率，选择指纹图像覆盖率最高的指纹图像作为目标指纹图像。
另一方面，终端可按照至少两个图像质量评价指标对多个指纹图像中的每一指纹图像进行图像质量评价，以得到多个图像质量评价值，选择最大的 图像质量评值对应的指纹图像作为目标指纹图像。即利用用于评价指纹图像的至少两个图像质量评价指标决策出多个指纹图像中图像质量最好的目标指纹图像。
具体地，利用如下公式分别计算出多个指纹图像中的每一指纹图像的质量评价值，将多个质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，公式如下：
Figure PCTCN2017079612-appb-000001
其中，S表示质量评价值，K表示图像质量评价指标的个数，Pi表示第i个所述图像质量评价指标的评价值，
Figure PCTCN2017079612-appb-000002
表示第i个图像质量评价指标的权重，其中，
Figure PCTCN2017079612-appb-000003
其中，K为大于1的整数。
103：在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
本发明实施例中，在目标指纹图像与预设指纹图像匹配成功时，终端可对该终端进行解锁。
其中，在目标指纹图像与预设指纹图像匹配时，可确定目标指纹图像和预设指纹图像之间的匹配值，若匹配值达到某个阈值，则可认为匹配成功，若匹配值未达到该某个阈值，则可认为指纹特征与预设指纹特征不匹配。在目标指纹图像与预设指纹图像匹配时，还可将目标指纹图像的指纹纹路与预设指纹图像的指纹纹路进行匹配，若匹配值达到某个阈值，则可认为目标指纹图像的指纹纹路与预设指纹图像的指纹纹路匹配成功，若匹配值未达到该某个阈值，则可认为目标指纹图像的指纹纹路与预设指纹图像的指纹纹路不匹配。在目标指纹图像与预设指纹图像匹配时，可提取目标指纹图像的特征点，例如Harris角点、尺度不变特征变换(Scale-invariant feature transform，SIFT)角点，那么，可比对采集的目标指纹图像的特征点和预设指纹图像的特征点进行匹配，若匹配值达到某个阈值，则可认为目标指纹图像的特征点与预设指纹图像的特征点匹配成功，若匹配值未达到该某个阈值，则可认为目标指纹图像的特征点与预设指纹图像的特征点不匹配。
通过本发明实施例在检测到指纹识别模组被按压时，通过调节指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，确定出该多个指纹图像中图像质量最好的目标指纹图像，并在目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。从而，可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配时，可提高两者之间的匹配成功率，即提高指纹解锁的效率，尤其，在用户的手指的指纹为干手指的指纹或者湿手指的指纹时，可减少用户按压指纹识别模组的次数，因而，提升了指纹解锁的效率，减少了指纹解锁消耗的时间。
请参阅图2，为本发明实施例提供的一种指纹解锁的方法的第二实施例流程示意图。本实施例中所描述的指纹解锁的方法，包括以下步骤：
201：在检测到指纹识别模组被按压时，判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹。
本发明实施例中，在终端检测到指纹识别模组被按压时，可判断按压该指纹识别模组的指纹是来自于干手指或者湿手指，由于干手指的指纹图像中的指纹纹路断断续续，而湿手指的指纹图像的指纹图像较大面积指纹纹路模糊化，几乎分不清指纹纹路，因而，可通过对指纹图像进行分析，判断出指纹图像是否来自于干手指或者湿手指。
可选地，终端可通过提取按压指纹识别模组的指纹的纹路特征，判断的指纹是否来自于干手指或者湿手指。若指纹图像的纹路断断续续，则该指纹图像属于干手指，若指纹图像中出现较大面积的指纹纹路模糊化时，则该指纹图像属于湿手指。
可选地，终端可通过提取按压指纹识别模组的指纹的特征点的个数，通过特征点的个数判断处于预设范围。其中，该预设范围可为小于第一阈值，例如，第一阈值可为预设指纹图像的特征点个数的某个百分比，例如，50％，或者，第一阈值为系统默认的某个值。进一步地，该预设范围可为处于第二阈值和第三阈值之间，其中，第二阈值小于第三阈值，第三阈值可为预设指纹图像的特征点个数的某个百分比，例如，50％，或者，第三阈值为系统默认的某个值，第二阈值可为预设指纹图像的特征点个数的某个百分比，例如，30％，或者，第二阈值为系统默认的某个值。在通常情况下，干手指或者湿手指的特征点个 数较少，终端可提取指纹的特征点的个数，例如，若该特征点的个数小于第一阈值，则说明该指纹的来自于干手指或者湿手指。
进一步地，在检测到指纹识别模组被按压时，在按压指纹识别模组的指纹不为干手指的指纹或者湿手指的指纹，则终端可直接采用默认的调节参数采集指纹，以得到指纹图像，将该指纹图像与预设指纹图像进行匹配，在匹配成功时，对终端进行解锁。
202：若是，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像。
203：确定所述多个指纹图像中图像质量最好的目标指纹图像。
204：在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
其中，图2中所描述的步骤202-步骤204可参考图1中所描述的步骤101-步骤103。
通过本发明实施例在检测到指纹识别模组被按压时，在按压指纹识别模组的手指来自于干手指或者湿手指时，通过调节指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，确定出该多个指纹图像中图像质量最好的目标指纹图像，并在目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。从而，可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配时，可提高两者之间的匹配成功率，即提高指纹解锁的效率，尤其，在用户的手指的指纹为干手指的指纹或者湿手指的指纹时，可减少用户按压指纹识别模组的次数，因而，提升了指纹解锁的效率，减少了指纹解锁消耗的时间。
请参阅图3，为本发明实施例提供的一种指纹解锁的方法的第三实施例流程示意图。本实施例中所描述的指纹解锁的方法，包括以下步骤：
301：在检测到指纹识别模组被按压时，判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹。
302：若是，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像。
303：利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
304：在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
其中，图3中所描述的步骤301可参考图2中所描述的步骤201，图3中所描述的步骤302-步骤304可参考图1中所描述的步骤101-步骤103。
通过本发明实施例在检测到指纹识别模组被按压时，在按压指纹识别模组的手指来自于干手指或者湿手指时，通过调节指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，利用至少两个图像质量评价指标决策出该多个指纹图像中图像质量最好的目标指纹图像，并在目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。从而，可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配时，可提高两者之间的匹配成功率，即提高指纹解锁的效率，尤其，在用户的手指的指纹为干手指的指纹或者湿手指的指纹时，可减少用户按压指纹识别模组的次数，因而，提升了指纹解锁的效率，减少了指纹解锁消耗的时间。
请参阅图4a，为本发明实施例提供的一种终端的第一实施例结构示意图。本实施例中所描述的终端400，包括采集单元401、确定单元402、解锁单元403。
采集单元401，用于在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
确定单元402，用于确定所述采集单元401采集的所述多个指纹图像中图像质量最好的目标指纹图像；
解锁单元403，用于在所述确定单元402确定的所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
可选地，所述调节参数至少包括数模转换偏移量和数模转换增量，其中，所述数模转换偏移量包含M个第一调节档位，所述数模转换增量包含N个第二调节档位，其中，所述M和所述N均为大于1的整数；
所述采集单元401通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，具体包括：
通过多次从所述M个第一调节档位中的选取的任一所述第一调节档位和所述N个第二调节档位中的任一所述第二调节档位采集指纹，以得到多个指纹图像。
可选地，所述确定单元402确定所述采集单元401采集的所述多个指纹图像中图像质量最好的目标指纹图像，具体包括：
利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
可选地，所述确定单元402确定所述采集单元401采集的所述多个指纹图像中图像质量最好的目标指纹图像，还具体包括：
利用如下公式分别计算出所述多个指纹图像中的每一指纹图像的图像质量评价值，将所述图像质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，所述公式如下：
Figure PCTCN2017079612-appb-000004
其中，所述S表示所述质量评价值，所述K表示所述图像质量评价指标的个数，所述Pi表示第i个所述图像质量评价指标的图像质量评价值，所述
Figure PCTCN2017079612-appb-000005
表示第i个所述图像质量评价指标的权重，其中，
Figure PCTCN2017079612-appb-000006
作为一种可能的实施方式，如图4b所示，图4a中所描述的终端还可包括：
判断单元404，用于在检测到指纹识别模组被按压时，判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，在所述判断单元404的判断结果为是时，由所述采集单元401通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像。
可选地，判断单元401具体用于：
通过提取按压所述指纹识别模组的指纹的纹路特征判断所述指纹是否来自于干手指或者湿手指；
或者，
通过提取按压所述指纹识别模组的指纹的特征点的个数，判断所述特征点的个数是否处于预设范围。
通过本发明实施例所描述的终端可在检测到指纹识别模组被按压时，通过调节指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图 像，确定出该多个指纹图像中图像质量最好的目标指纹图像，并在目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。从而，可通过调节调节参数得到质量最好的目标指纹图像，因此，在该目标指纹图像与预设指纹图像进行匹配时，可提高两者之间的匹配成功率，即提高指纹解锁的效率，尤其，在用户的手指的指纹为干手指的指纹或者湿手指的指纹时，可减少用户按压指纹识别模组的次数，因而，提升了指纹解锁的效率，减少了指纹解锁消耗的时间。
请参阅图5，为本发明实施例提供的一种终端的第二实施例结构示意图。本实施例中所描述的终端500，包括：至少一个输入设备1000；至少一个输出设备2000；至少一个处理器3000，例如CPU；和存储器4000，上述输入设备1000、输出设备2000、处理器3000和存储器4000通过总线5000连接。
其中，上述输入设备1000具体可为触控面板、物理按键、键盘、鼠标或者指纹识别模组。
上述输出设备2000具体可为显示屏。
上述存储器4000可以是高速RAM存储器，也可为非不稳定的存储器(non-volatile memory)，例如磁盘存储器。上述存储器4000用于存储一组程序代码，上述输入设备1000、输出设备2000和处理器3000用于调用存储器4000中存储的程序代码，执行如下操作：
上述处理器3000，用于：
在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
确定所述多个指纹图像中图像质量最好的目标指纹图像；
在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
可选地，所述调节参数至少包括数模转换偏移量和数模转换增量，其中，所述数模转换偏移量包含M个第一调节档位，所述数模转换增量包含N个第二调节档位，其中，所述M和所述N均为大于1的整数；
上述处理器3000通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，包括：
通过多次从所述M个第一调节档位中的选取的任一所述第一调节档位和所述N个第二调节档位中的任一所述第二调节档位采集指纹，以得到多个指 纹图像。
可选地，上述处理器3000确定所述多个指纹图像中图像质量最好的目标指纹图像，包括：
利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
进一步可选地，上述处理器3000利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像，包括：
利用如下公式分别计算出所述多个指纹图像中的每一指纹图像的图像质量评价值，将所述图像质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，所述公式如下：
Figure PCTCN2017079612-appb-000007
其中，所述S表示所述质量评价值，所述K表示所述图像质量评价指标的个数，所述Pi表示第i个所述图像质量评价指标的图像质量评价值，所述
Figure PCTCN2017079612-appb-000008
表示第i个所述图像质量评价指标的权重，其中，
Figure PCTCN2017079612-appb-000009
可选地，上述处理器3000在检测到指纹识别模组被按压时，还具体用于：
判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，若是，执行所述通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像的步骤。
可选地，上述处理器3000判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，包括：
通过提取按压所述指纹识别模组的指纹的纹路特征判断所述指纹是否来自于干手指或者湿手指；
或者，
通过提取按压所述指纹识别模组的指纹的特征点的个数，判断所述特征点的个数是否处于预设范围。
具体实现中，本发明实施例中所描述的输入设备1000、输出设备2000和处理器3000可执行本发明实施例提供的一种指纹解锁的方法的第一实施例、第二实施例和第三实施例中所描述的实现方式，也可执行本发明实施例提供的一种终端的第一实施例、第二实施例和第三实施例中所描述的终端的实现方式，在此不再赘述。
本发明实施例还提供一种计算机存储介质，其中，该计算机存储介质可存储有程序，该程序执行时包括上述方法实施例中记载的任意一种指纹解锁的方法的部分或全部步骤。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
需要说明的是，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定是本发明所必须的。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置，可通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中， 也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范。

Claims (22)

  1. 一种指纹解锁的方法，其特征在于，包括：
    在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
    确定所述多个指纹图像中图像质量最好的目标指纹图像；
    在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
  2. 根据权利要求1所述的方法，其特征在于，所述调节参数至少包括数模转换偏移量和数模转换增量，其中，所述数模转换偏移量包含M个第一调节档位，所述数模转换增量包含N个第二调节档位，其中，所述M和所述N均为大于1的整数；
    所述通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像，包括：
    通过多次从所述M个第一调节档位中的选取的任一所述第一调节档位和所述N个第二调节档位中的任一所述第二调节档位采集指纹，以得到多个指纹图像。
  3. 根据权利要求1或2所述的方法，其特征在于，所述目标指纹图像是所述多个指纹图像中清晰度最高的指纹图像；或者，所述目标指纹图像是所述多个指纹图像中信噪比最高的指纹图像；或者，所述目标指纹图像是指纹图像覆盖率最高的指纹图像；或者，所述目标指纹图像是纹路清晰度最高的指纹图像。
  4. 根据权利要求1或2所述的方法，其特征在于，所述确定所述多个指纹图像中图像质量最好的目标指纹图像，包括：
    利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
  5. 根据权利要求4所述的方法，其特征在于，所述利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像，包括：
    利用如下公式分别计算出所述多个指纹图像中的每一指纹图像的图像质量评价值，将所述图像质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，所述公式如下：
    Figure PCTCN2017079612-appb-100001
    其中，所述S表示所述质量评价值，所述K表示所述图像质量评价指标的个数，所述Pi表示第i个所述图像质量评价指标的图像质量评价值，所述
    Figure PCTCN2017079612-appb-100002
    表示第i个所述图像质量评价指标的权重，其中，
    Figure PCTCN2017079612-appb-100003
  6. 根据权利要求5所述的方法，其特征在于，所述在检测到指纹识别模组被按压时，所述方法还包括：
    判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，若是，执行所述通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像的步骤。
  7. 根据权利要求6所述的方法，其特征在于，所述判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，包括：
    通过提取按压所述指纹识别模组的指纹的纹路特征判断所述指纹是否来自于干手指或者湿手指；
    或者，
    通过提取按压所述指纹识别模组的指纹的特征点的个数，判断所述特征点的个数是否处于预设范围。
  8. 一种终端，其特征在于，包括：
    采集单元，用于在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像；
    确定单元，用于确定所述采集单元采集的所述多个指纹图像中图像质量最好的目标指纹图像；
    解锁单元，用于在所述确定单元确定的所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
  9. 根据权利要求8所述的终端，其特征在于，所述调节参数至少包括数模转换偏移量和数模转换增量，其中，所述数模转换偏移量包含M个第一调节档位，所述数模转换增量包含N个第二调节档位，其中，所述M和所述N均为大于1的整数；
    所述确定单元具体用于：
    通过多次从所述M个第一调节档位中的选取的任一所述第一调节档位和所述N个第二调节档位中的任一所述第二调节档位采集指纹，以得到多个指纹图像。
  10. 根据权利要求8或9所述的终端，其特征在于，所述目标指纹图像是所述多个指纹图像中清晰度最高的指纹图像；或者，所述目标指纹图像是所述多个指纹图像中信噪比最高的指纹图像；或者，所述目标指纹图像是指纹图像覆盖率最高的指纹图像；或者，所述目标指纹图像是纹路清晰度最高的指纹图像。
  11. 根据权利要求8或9所述的终端，其特征在于，所述确定单元具体用于：
    利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
  12. 根据权利要求11所述的终端，其特征在于，所述确定单元还具体用于：
    利用如下公式分别计算出所述多个指纹图像中的每一指纹图像的图像质量评价值，将所述图像质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，所述公式如下：
    Figure PCTCN2017079612-appb-100004
    其中，所述S表示所述质量评价值，所述K表示所述图像质量评价指标的个数，所述Pi表示第i个所述图像质量评价指标的图像质量评价值，所述
    Figure PCTCN2017079612-appb-100005
    表示第i个所述图像质量评价指标的权重，其中，
    Figure PCTCN2017079612-appb-100006
  13. 根据权利要求12所述的终端，其特征在于，所述终端还包括：
    判断单元，用于在检测到指纹识别模组被按压时，判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，在所述判断单元的判断结果为是时，由所述采集单元通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像。
  14. 根据权利要求13所述的终端，其特征在于，所述判断单元具体用于：
    通过提取按压所述指纹识别模组的指纹的纹路特征判断所述指纹是否来自于干手指或者湿手指；
    或者，
    通过提取按压所述指纹识别模组的指纹的特征点的个数，判断所述特征点的个数是否处于预设范围。
  15. 一种终端，其特征在于，包括：
    存储有可执行程序代码的存储器；
    与所述存储器耦合的处理器；
    所述处理器调用所述存储器中存储的所述可执行程序代码执行以下操作：
    在检测到指纹识别模组被按压时，通过调节所述指纹识别模组中的指纹采 集芯片的调节参数采集指纹，以得到多个指纹图像；
    确定所述多个指纹图像中图像质量最好的目标指纹图像；
    在所述目标指纹图像与预设指纹图像匹配成功时，对终端进行解锁。
  16. 根据权利要求15所述的终端，其特征在于，所述调节参数至少包括数模转换偏移量和数模转换增量，其中，所述数模转换偏移量包含M个第一调节档位，所述数模转换增量包含N个第二调节档位，其中，所述M和所述N均为大于1的整数；
    所述处理器通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像的具体实施方式有：
    通过多次从所述M个第一调节档位中的选取的任一所述第一调节档位和所述N个第二调节档位中的任一所述第二调节档位采集指纹，以得到多个指纹图像。
  17. 根据权利要求15或16所述的终端，其特征在于，所述目标指纹图像是所述多个指纹图像中清晰度最高的指纹图像；或者，所述目标指纹图像是所述多个指纹图像中信噪比最高的指纹图像；或者，所述目标指纹图像是指纹图像覆盖率最高的指纹图像；或者，所述目标指纹图像是纹路清晰度最高的指纹图像。
  18. 根据权利要求15或16所述的终端，其特征在于，所述处理器确定所述多个指纹图像中图像质量最好的目标指纹图像的具体实施方式有：
    利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像。
  19. 根据权利要求18所述的终端，其特征在于，所述处理器利用用于评价指纹图像的至少一个图像质量评价指标决策出所述多个指纹图像中图像质量最好的目标指纹图像的具体实施方式有：
    利用如下公式分别计算出所述多个指纹图像中的每一指纹图像的图像质 量评价值，将所述图像质量评价值中的最大值对应的指纹图像作为图像质量最好的目标指纹图像，其中，所述公式如下：
    Figure PCTCN2017079612-appb-100007
    其中，所述S表示所述质量评价值，所述K表示所述图像质量评价指标的个数，所述Pi表示第i个所述图像质量评价指标的图像质量评价值，所述
    Figure PCTCN2017079612-appb-100008
    表示第i个所述图像质量评价指标的权重，其中，
    Figure PCTCN2017079612-appb-100009
  20. 根据权利要求19所述的终端，其特征在于，所述在检测到指纹识别模组被按压时，所述处理器还执行以下步骤：
    判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹，若是，执行所述通过调节所述指纹识别模组中的指纹采集芯片的调节参数采集指纹，以得到多个指纹图像的步骤。
  21. 根据权利要求20所述的终端，其特征在于，所述处理器判断按压所述指纹识别模组的指纹是是否为干手指的指纹或者湿手指的指纹的具体实施方式有：
    通过提取按压所述指纹识别模组的指纹的纹路特征判断所述指纹是否来自于干手指或者湿手指；
    或者，
    通过提取按压所述指纹识别模组的指纹的特征点的个数，判断所述特征点的个数是否处于预设范围。
  22. 一种计算机存储介质，其特征在于，所述计算机存储介质用于存储如权15～权21任一项所描述的终端所用的软件指令，所述软件指令包含用于执行如权利要求1至权利要求7任一项所描述的指纹解锁的方法所设计的程序。
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