WO2022246666A1 - 生物特征采集方法、芯片及计算机可读存储介质 - Google Patents

生物特征采集方法、芯片及计算机可读存储介质 Download PDF

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Publication number
WO2022246666A1
WO2022246666A1 PCT/CN2021/095876 CN2021095876W WO2022246666A1 WO 2022246666 A1 WO2022246666 A1 WO 2022246666A1 CN 2021095876 W CN2021095876 W CN 2021095876W WO 2022246666 A1 WO2022246666 A1 WO 2022246666A1
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WIPO (PCT)
Prior art keywords
value
area
parameter
pixels
biometric
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PCT/CN2021/095876
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English (en)
French (fr)
Inventor
青小刚
吕蒙
袁超
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深圳市汇顶科技股份有限公司
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Priority to EP21904612.5A priority Critical patent/EP4120124B1/en
Priority to PCT/CN2021/095876 priority patent/WO2022246666A1/zh
Priority to US17/848,379 priority patent/US11776306B2/en
Publication of WO2022246666A1 publication Critical patent/WO2022246666A1/zh

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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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1394—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using acquisition arrangements
    • 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
    • G06V40/1318—Sensors therefor using electro-optical elements or layers, e.g. electroluminescent 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
    • 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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1388—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing
    • 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
    • G06V40/60—Static or dynamic means for assisting the user to position a body part for biometric acquisition
    • G06V40/67—Static or dynamic means for assisting the user to position a body part for biometric acquisition by interactive indications to the user

Definitions

  • the embodiments of the present application relate to the technical field of biometric feature detection, and in particular to a biometric feature collection method, a chip, and a computer-readable storage medium.
  • the biometric technology has become a new interactive technology
  • the optical fingerprint recognition technology has become a very convenient and fast fingerprint recognition scheme.
  • the optical fingerprint recognition technology adopts the hidden fingerprint design under the screen, and the finger can be unlocked by directly pressing the fingerprint icon area displayed on the screen.
  • More and more mobile phone projects of complete machine manufacturers support the optical fingerprint recognition function, and also introduce screens produced by different manufacturers. The screens produced by different manufacturers are quite different.
  • a default exposure time is set for the biometric feature collection chip in the whole machine.
  • the adaptability of the chip to changes in the external environment becomes poor, which affects the accuracy of the collected biometric images and reduces the accuracy of subsequent biometric identification or registration.
  • the under-screen fingerprint collection chip in the mobile phone Take the under-screen fingerprint collection chip in the mobile phone as an example, the fluctuation of fingerprint light spots will easily lead to poor adaptability of the under-screen fingerprint collection chip to fingerprint light spots, affecting the accuracy of the collected fingerprint images, and reducing the subsequent fingerprint identification or registration. the accuracy rate.
  • the purpose of the embodiments of the present application is to provide a biometric feature collection method, a chip and a computer-readable storage medium, so that the accuracy of the collected biometric feature images can be improved, and the accuracy of subsequent biometric feature recognition or registration can be increased.
  • the embodiment of the present application provides a biological feature collection method, which is applied to a biological feature collection chip, including: acquiring configuration parameters; wherein, the configuration parameters include: the first exposure duration, the first area and A target photosensitivity value, the first area being a local area in the photosensitive area of the biometric feature collection chip; exposing the first area according to the first exposure time length, and acquiring the photosensitivity value of the first area ; According to the photosensitivity value of the first area and the first exposure duration, determine the second exposure duration required to collect the target photosensitivity value in the photosensitive region; according to the second exposure duration, collect biological characteristics image.
  • the configuration parameters include: the first exposure duration, the first area and A target photosensitivity value, the first area being a local area in the photosensitive area of the biometric feature collection chip; exposing the first area according to the first exposure time length, and acquiring the photosensitivity value of the first area ; According to the photosensitivity value of the first area and the first exposure duration, determine the second exposure duration required to collect the target photosensitivity value in the photosensitive region; according
  • the embodiment of the present application also provides a biological feature collection chip, including: a processing unit and a storage unit connected to the processing unit, the storage unit stores instructions executable by the processing unit, and the instructions are executed by The processing unit executes, so that the processing unit can execute the above biometric feature collection method.
  • Embodiments of the present application also provide a terminal, including the above biometric feature collection chip.
  • Embodiments of the present application also provide a computer-readable storage medium storing a computer program, and implementing the above biometric feature collection method when the computer program is executed by a processor.
  • the first exposure duration in the configuration parameters when collecting biometric images, firstly, according to the first exposure duration in the configuration parameters, partial exposure is performed on a local area (i.e., the first area) in the photosensitive area of the biometric acquisition chip to obtain the first Sensitivity value of the area.
  • the photosensitivity value of the first area and the first exposure duration therefore, according to the photosensitivity value of the first area and the first exposure duration, the second exposure required to acquire the target photosensitivity value in the photosensitive area can be reasonably and accurately determined duration. That is to say, the collection of biometric images is not based on the default exposure time at the factory, but based on the second exposure time obtained in the current environment, so that the collected biometric images are more accurate. .
  • the second exposure time It can adapt to changes in the external environment, thereby improving the adaptability of the biometric feature acquisition chip to the external environment, reducing the impact of changes in the external environment on the acquisition performance, and helping to improve the accuracy of subsequent biometric feature identification or registration.
  • the first area is a local area in the photosensitive area, the local exposure speed is faster, which can speed up the acquisition of biometric images to a certain extent, thereby speeding up the subsequent biometric identification or registration.
  • Fig. 1 is the schematic diagram of the fingerprint spot mentioned in the embodiment of the present application.
  • Fig. 2 is a flow chart of a biometric collection method mentioned in the embodiment of the present application.
  • Fig. 3 is a schematic diagram of the relationship between the first region and the photosensitive region mentioned in the embodiment of the present application;
  • Fig. 4 is a schematic diagram of the marking information of each pixel in the first area mentioned in the embodiment of the present application.
  • Fig. 5 is a schematic diagram of the bad block area in the first area mentioned in the embodiment of the present application.
  • Fig. 6 is a schematic diagram of the linear relationship between the photosensitivity value and the exposure time mentioned in the embodiment of the present application.
  • Fig. 7 is a flow chart of another biometric collection method mentioned in the embodiment of the present application.
  • FIG. 8 is a flowchart of an implementation of step 706 mentioned in the embodiment of the present application.
  • Fig. 9 is a schematic diagram of the distribution of the first area and the second area in the photosensitive area mentioned in the embodiment of the present application.
  • FIG. 10 is a flowchart of an implementation of step 802 mentioned in the embodiment of the present application.
  • Fig. 11 is a schematic diagram of the stripe image mentioned in the embodiment of the present application.
  • Fig. 12 is a flow chart of an implementation method of collecting biometric images according to the second exposure time mentioned in the embodiment of the present application;
  • Fig. 13 is a flow chart of a biometric feature collection method applied to an off-screen fingerprint collection chip mentioned in the embodiment of the present application;
  • FIG. 14 is a schematic structural diagram of the biological feature collection chip mentioned in the embodiment of the present application.
  • the off-screen biometric acquisition technology is to set the biometric acquisition chip under the screen, and collect images of external objects through the biometric acquisition chip, so as to realize Subsequent biometric or biometric enrollment.
  • biometric identification may include: fingerprint identification, palmprint identification, iris identification, face identification, etc.
  • OLED Organic Light-Emitting Diode
  • LCD Liquid Crystal Display
  • OLED screen is a current-type organic light-emitting device, which can control each display unit (also called a pixel) to emit light independently through a display driving module.
  • the biometric feature collection chip is a fingerprint collection chip.
  • Terminals with OLED screens can realize off-screen optical fingerprint collection, and the fingerprint collection chip is set under the OLED screen, so the fingerprint collection chip can also be called an off-screen fingerprint collection chip, and the pixels in the OLED screen can be used as fingerprint excitation light sources Light the screen.
  • the pixels located in the fingerprint detection area (also known as the photosensitive area) of the OLED screen are driven to emit light to display a fingerprint spot in the fingerprint detection area, and the emitted light is used as excitation light for fingerprint identification to irradiate the finger above the OLED screen, After being scattered, reflected or transmitted by the finger, the fingerprint detection light carrying the fingerprint information of the finger is formed.
  • the fingerprint detection light returns to the OLED screen and is transmitted to the fingerprint acquisition chip below through the OLED screen.
  • the fingerprint acquisition chip can receive the fingerprint detection light And convert the fingerprint detection light into the corresponding electrical signal, so as to realize the fingerprint image collection.
  • the schematic diagram of the above-mentioned fingerprint spot can be seen in Figure 1.
  • a terminal with an off-screen fingerprint acquisition chip will set a default exposure time at the factory based on the result of the calibration of the whole machine during the mass production stage of the whole machine, and the default exposure time will be stored in the terminal. After the terminal leaves the factory, when the user uses the terminal for fingerprint registration or fingerprint identification, the fingerprint image will be collected based on the default exposure time stored in the terminal.
  • the inventors of the present application found that if the fingerprint spot fluctuates when the user is using the terminal, the accuracy of fingerprint recognition is likely to be low.
  • the fluctuation of the fingerprint light spot may include: the brightness fluctuation and the color temperature fluctuation of the fingerprint light spot.
  • Fluctuations in fingerprint spots may include: the default exposure time set at the factory is inaccurate due to abnormal fingerprint spots in the whole machine calibration stage; during user use, the terminal is in an environment such as switching wallpapers, screen aging, and software updates.
  • the inventor found through research that the reason why the accuracy rate of fingerprint recognition is low due to fluctuations in fingerprint light spots is that the fingerprint acquisition chip under the screen is still based on the default exposure set at the factory when the terminal is being used by the user after leaving the factory. The fingerprint image will be collected for a long time, and the default exposure time will not be adjusted during use, resulting in poor adaptability of the under-screen fingerprint collection chip to fingerprint light spots, resulting in a lower accuracy of fingerprint recognition.
  • this application implements The example provides a biometric feature collection method, which is applied to a biometric feature collection chip, including: obtaining configuration parameters; wherein, the configuration parameters include: a first exposure duration, a first area, and a target photosensitive value, and the first area is a biometric feature collection chip The local area in the photosensitive area; according to the first exposure time, the first area is exposed, and the photosensitive value of the first area is obtained; according to the photosensitive value of the first area and the first exposure time, it is determined that the target photosensitive area is collected in the photosensitive area The second exposure time required by the value; according to the second exposure time, a biometric image is collected.
  • the configuration parameters include: a first exposure duration, a first area, and a target photosensitive value, and the first area is a biometric feature collection chip
  • the local area in the photosensitive area according to the first exposure time, the first area is exposed, and the photosensitive value of the first area is obtained; according to the photosensitive value of the first area and the first exposure time, it is
  • the application scenarios of this embodiment may include: scenarios requiring biometric image acquisition, such as biometric identification, biometric registration, and the like.
  • Biometric identification and biometric registration can be fingerprint identification, fingerprint registration, face recognition, face registration, etc.
  • the process of biometric feature collection in this embodiment may be triggered, that is, start to acquire configuration parameters.
  • the biometric feature collection chip when the biometric feature collection chip collects the biometric feature image, it first performs local exposure on the partial area (ie, the first area) in the photosensitive area of the biometric feature collection chip according to the first exposure time in the configuration parameters. , to obtain the photosensitivity value of the first area.
  • the second exposure required to acquire the target photosensitivity value in the photosensitive area can be reasonably and accurately determined duration. That is to say, the collection of biometric images is not based on the default exposure time at the factory, but based on the second exposure time obtained in the current environment, so that the collected biometric images are more accurate. .
  • the second exposure time It can adapt to changes in the external environment, thereby improving the adaptability of the biometric feature acquisition chip to the external environment, reducing the impact of changes in the external environment on the acquisition performance, and helping to improve the accuracy of subsequent biometric feature identification or registration.
  • the first area is a local area in the photosensitive area, the speed of local exposure is relatively fast, which can speed up the collection of biometric images to a certain extent, thereby speeding up the speed of subsequent biometric identification or registration.
  • the biometric feature collection chip is an off-screen fingerprint collection chip
  • the biometric feature image collected by the off-screen fingerprint collection chip can be used for fingerprint identification or fingerprint registration.
  • the biometric feature collection chip can also be an iris feature collection chip, a palmprint feature collection chip, a face feature collection chip, etc.
  • the flow chart of the biological feature collection method can refer to Figure 2, including:
  • Step 201 Obtain configuration parameters.
  • Step 202 Expose the first area according to the first exposure time, and acquire the sensitivity value of the first area.
  • Step 203 According to the photosensitivity value of the first area and the first exposure duration, determine the second exposure duration required to acquire the target photosensitivity value in the photosensitivity region.
  • Step 204 Acquire biometric images according to the second exposure time.
  • the configuration parameters in step 201 include: a first exposure duration, a first area and a target light-sensing value, and the first area is a partial area in the light-sensing area of the biometric feature collection chip.
  • Configuration parameters can be preset by those skilled in the art according to actual needs.
  • obtaining configuration parameters in step 201 includes: obtaining configuration parameters after a preset trigger condition is detected; wherein, the preset trigger condition includes: biometric registration and/or biometric identification are required . That is, the biometric feature collection chip acquires configuration parameters after determining that biometric registration and/or biometric identification is required.
  • the manner in which the biometric feature collection chip determines that biometric feature registration is required may be as follows: the biometric feature collection chip receives notification information that the user needs to perform biometric feature registration, and the notification information may be sent by a processor in the terminal, wherein the processor may be the terminal Central processing unit (Central Processing Unit, CPU), microprocessor, coprocessor, etc.
  • the terminal may be a device such as a mobile phone or a tablet computer.
  • the manner in which the biometric feature acquisition chip determines that biometric feature identification is required may be: the biometric feature acquisition chip determines that the terminal needs to be unlocked based on biometric feature identification, and needs to be paid based on biometric feature identification.
  • the preset trigger condition may also include: the biometrics collection chip detects that it is activated, and when the biometrics collection chip detects that it is activated, acquire configuration parameters.
  • acquiring configuration parameters in step 201 includes: acquiring internally stored configuration parameters when a preset trigger condition is detected.
  • the configuration parameters can be pre-stored in the biometrics collection chip, for example, the preset configuration parameters can be written into the registers of the biometrics collection chip. That is to say, the biometric feature collection chip can obtain the configuration parameters by itself, which is conducive to quickly obtaining the configuration parameters.
  • acquiring configuration parameters in step 201 includes: receiving configuration parameters delivered by application software in the terminal.
  • the configuration parameters are issued by the application software, and the biometric acquisition chip does not need to store these configuration parameters, which is beneficial to save costs and storage space, and it is convenient to modify the configuration parameters through the application software according to actual needs, which improves the convenience of modifying the configuration parameters.
  • the configuration parameters delivered by the application software in the receiving terminal may be: configuration parameters delivered by the receiving software terminal when a preset trigger condition is detected.
  • the software side can issue configuration parameters to the biometrics collection chip after detecting preset trigger conditions, which have been described above. I won't repeat them here.
  • the biometric feature collection chip can be in a dormant state when no data collection is required. When biometric feature collection is required, the biometric feature collection chip is awakened, and the software side begins to issue configuration parameters.
  • the biometrics collection chip after the biometrics collection chip receives the configuration parameters from the software side, it can store the configuration parameters in the register. When the preset trigger condition is detected again later, the biometrics collection chip can directly read the The configuration parameters are obtained from the registers in the feature acquisition chip, without having to be issued by the software every time, which is conducive to improving the convenience of obtaining configuration parameters.
  • the biometrics collection chip is an off-screen fingerprint collection chip
  • the need for biometrics registration and/or the need for biometrics identification includes: detecting that the area where the fingerprint spot on the screen is pressed is pressed, and the preset duration is longer than or It is equal to the minimum time required for the fingerprint light spot to be illuminated until the fingerprint light spot becomes stable.
  • the acquisition of configuration parameters in step 201 includes: after detecting that the area where the fingerprint light spot on the screen is located is pressed, the configuration parameters are acquired at intervals of a preset period of time.
  • the minimum time required for the fingerprint light spot to be lighted up to the fingerprint light spot to be stable can be tested by those skilled in the art according to actual needs, for example, it can be set to 40ms to 50ms, but this embodiment does not specifically limit it.
  • the fingerprint acquisition chip under the screen determines that fingerprint identification or fingerprint registration is currently required.
  • the configuration parameters are obtained after the interval is preset, which is beneficial to ensure that after the fingerprint spot displayed on the screen is stable, the fingerprint acquisition chip under the screen obtains the configuration parameters again, and then calculates the subsequent second exposure time based on the configuration parameters.
  • the second exposure time is obtained after the fingerprint spot is stabilized, which improves the accuracy of the acquired second exposure time, thereby improving the accuracy of the collected fingerprint image, so as to improve the accuracy of subsequent fingerprint identification or fingerprint registration.
  • the fingerprint collection chip under the screen can detect that the area where the fingerprint spot is located is pressed, and then send the pressed information to the software side, and the software side starts timing when it receives the pressed information. After the preset time is reached, the configuration parameters are sent to the under-screen fingerprint acquisition chip, so that the under-screen fingerprint acquisition chip can obtain the configuration parameters at preset intervals after detecting that the area where the fingerprint spot on the screen is located is pressed.
  • the configuration parameters are issued by the software side, and the fingerprint acquisition chip under the screen does not need to store these configuration parameters, which is beneficial to save costs and storage space.
  • the software side sends configuration parameters to the under-screen fingerprint acquisition chip, so that the second exposure time is obtained after the fingerprint spot is stabilized, which improves the accuracy of the second exposure time, thereby improving Accuracy of the collected fingerprint images to improve the accuracy of subsequent fingerprint identification or fingerprint registration.
  • the off-screen fingerprint collection chip can start timing when it detects that the area where the fingerprint light spot is located is pressed, and after the timing reaches the preset duration, obtain the pre-stored configuration parameters in the register from the register of the off-screen fingerprint collection chip , so that the under-screen fingerprint acquisition chip can acquire the configuration parameters at preset intervals after detecting that the area where the fingerprint spot on the screen is located is pressed.
  • the fingerprint acquisition chip under the screen can obtain the configuration parameters by itself without interacting with the software terminal, which is beneficial to quickly obtain the configuration parameters.
  • the fingerprint acquisition chip under the screen can obtain the configuration parameters again, making the second The exposure time is obtained after the fingerprint spot is stabilized, which improves the accuracy of the acquired second exposure time, thereby improving the accuracy of the collected fingerprint image, so as to improve the accuracy of subsequent fingerprint identification or fingerprint registration.
  • the first exposure duration (denoted as T1) may be determined according to the linearity of the biometric feature collection chip, the smaller the linearity, the smaller the determined first exposure duration.
  • Linearity is an important index to describe the biometric feature collection chip, and the smaller the linearity, the better the linearity, that is, the more accurate the linearity.
  • the linearity of the biometric feature acquisition chip will affect the accuracy of the light intensity estimated based on the collected photosensitivity value within the same exposure time, and the accuracy of the estimated light intensity will further affect the collected biometric features. Image Accuracy.
  • the first exposure duration is determined according to the linearity of the biometric feature collection chip, and the smaller the linearity, the smaller the determined first exposure duration, which is beneficial to improve the accuracy of the collected biometric image to a certain extent. , thereby improving the accuracy of subsequent biometric identification or registration.
  • the first exposure duration can also be determined according to the linearity of the biometric feature collection chip and the preset standard duration for fingerprint identification.
  • the standard time required for completing biometric identification may also be referred to as: Key Performance Indicator time (KPI time).
  • KPI time can be set by those skilled in the art according to actual needs. For example, when the requirement for recognition speed is high, the KPI time can be set shorter, and when the requirement for recognition speed is low, the KPI time can be set longer. The setting of time can meet the requirements for recognition speed in different recognition scenarios. The larger the KPI time, the longer T1 can be set, and the smaller the KPI time, the shorter T1 can be set.
  • the size of T1 can be determined by comprehensively considering KPI time and linear characteristics, and T1 is greater than 0 milliseconds.
  • the first exposure duration is greater than 0 milliseconds and less than or equal to 10 milliseconds. That is to say, the value range of the first exposure time T1 is between 0 and 10 milliseconds, and the value of T1 is small, which is beneficial to shorten the time for completing biometric feature collection, thereby shortening the time for subsequent biometric feature identification or registration . In a specific implementation, within a certain range (for example, between 0 and 10 milliseconds), the larger the value of T1, the more accurate the determined T2, and thus the more accurate the collected biometric image.
  • the first exposure duration T1 is determined according to the KPI time and the linearity of the biological feature collection chip, and 0ms ⁇ T1 ⁇ 10ms. That is to say, T1 selects one between 0ms and 10ms according to the KPI time and the linearity of the biological feature collection chip, which is conducive to speeding up the collection speed as much as possible while ensuring that the accuracy of the collection will not be affected. .
  • the biological feature collection chip is arranged under the screen, and the area of the first area is determined according to the structure of the screen, which is a soft screen or a hard screen.
  • the area of the first region determined based on the soft screen is larger than the area of the first region determined based on the hard screen. That is to say, the first area of the soft screen is larger than that of the hard screen. Due to the collapse of the center of the soft screen, the area of the first area taken by the hard screen is larger than that of the hard screen.
  • the center collapse of the soft screen makes the light sensitivity value collected by the pixel located in the center of the soft screen smaller, so the larger first area is taken. It makes it possible to combine the photosensitivity values collected by the pixels in the larger first region to obtain the photosensitivity value of the first region, which is conducive to adapting to the needs of different screen types for the size of the first region and improving the photosensitivity collected after partial exposure value accuracy.
  • the center of the first region 301 is the light-gathering center 303 of the photosensitive region 302 .
  • the focusing center 303 can be understood as the projection point of the center of the lens assembled with the biometric feature collection chip in the photosensitive area 302 . It can be understood that during the assembly process of the biometric feature collection chip and the lens, there may be assembly tolerances, so that the center of the lens does not completely coincide with the center of the photosensitive area in the biometric feature collection chip in the vertical direction.
  • the first area 301 is an area centered on the light-sensing center of the light-sensing area, and the light-sensing values collected by each pixel in the first area centered on the light-sensing center are relatively concentrated, and the difference is small, which is beneficial to improving the obtained second.
  • the accuracy of the sensitivity value of an area may also directly be the center of the photosensitive region.
  • the area of the first region determined based on the soft screen is greater than the area of the first region determined based on the hard screen, and the centers of the first regions in both the soft screen and the hard screen are the light-sensing centers of the photosensitive regions, It is beneficial to further improve the accuracy of the acquired photosensitive value of the first region while adapting to the requirements of different screen types on the size of the first region.
  • the larger the first area the more accurate the light intensity detection is, but the accuracy of the light intensity detection will not increase when the first area is large to a certain extent, and at the same time, the larger the first area is, the collected The biometric image takes longer.
  • the size of the first area can be determined through simulation, for example, the size of the first area can be gradually increased during the simulation process, and the accuracy of light intensity detection and the biometric image collected after each increase of the first area can be determined
  • the required time according to the accuracy of light intensity detection and the time required to collect the biometric image, take a compromise value for the first area, so that the determined first area can ensure that the time to collect the biometric image is not It will be too long, and it will not have a great impact on the accuracy of light intensity detection.
  • the number of pixels in the first region is an integer multiple of the number of pixels to be read out in a mode of one pixel determined based on the image readout mode binning of the biometric feature collection chip.
  • the image readout mode binning of the biometric feature collection chip is 2*2, that is, the number of pixels to be read out in the mode of one pixel is 4, and the number of pixels in the first area is an integer multiple of 4.
  • the image readout mode binning of the biometric feature collection chip is 4*4, that is, the number of pixels to be read out in the mode of one pixel is 16, and the number of pixels in the first area is an integer multiple of 16.
  • the selection of the first area takes into account the image readout mode binning of the biometric feature acquisition chip itself, which facilitates the subsequent processing of pixels in the first area based on binning, which is conducive to adapting to the image readout mode of the biometric feature acquisition chip itself and improving the image quality.
  • the speed of readout increases the speed at which biometric images are acquired.
  • the first area is a rectangular area, such as the rectangular area 301 in FIG. express. It can be understood that a pixel array including several pixels is distributed in the photosensitive area 302 , the pixel A is located in the x0th row and the y0th column in the pixel array, and the pixel B is located in the x1th row and the y1th column in the pixel array.
  • the configuration parameter of the first area is delivered by the software side, the software side can directly send the coordinates of the boundary points of the first area, such as the coordinates of the two points A and B in Figure 3, which can reduce the amount of data to be delivered. Increase the sending speed.
  • the configuration parameter of the first region is pre-stored in the biometrics collection chip, the coordinates of the boundary points of the first region can be stored in the biometrics collection chip, which can reduce the amount of stored data and save storage space.
  • the first area can also be represented by the marking information of the pixels in the entire photosensitive area, for example: all the pixels in the first area 301 are marked as "X”, and all the pixels in the photosensitive area 302 except the first area The pixels other than the pixels in 301 are marked as "Y”, and the pixels in the entire photosensitive area can be expressed as an array composed of "X” and "Y", and the area formed by "X” in the array is the first area 301. If the configuration parameter of the first area is issued by the software side, the software side can directly send the above-mentioned array composed of "X” and "Y", which is convenient for the biometric feature collection chip to directly receive the "X” and "Y” array.
  • the array composed of Y" clearly distinguishes the first area in the photosensitive area. If the configuration parameter of the first area is pre-stored in the biometrics collection chip, the above-mentioned array composed of "X” and “Y” can be stored in the biometrics collection chip, which facilitates the biometrics collection chip to be directly based on the stored The array of "X” and "Y” clearly identifies the first area in the photosensitive area.
  • the biometric feature collection chip is arranged under the screen, and the target photosensitive value is determined based on the gain value corresponding to the structure of the screen.
  • the structure of the screen is a soft screen or a hard screen, and the gain value corresponding to the soft screen is greater than the gain value corresponding to the hard screen. value.
  • the target photosensitive value is recorded as Target, and the gain value is recorded as Gain.
  • Gain can represent the amplification factor of the signal.
  • Gain and Target have a preset corresponding relationship, which can be set by those skilled in the art according to actual needs.
  • the gain value Gain of the screen may be stored in a register of the biometric feature collection chip.
  • the gain value corresponding to the soft screen is beneficial to ensure that the soft screen and the hard screen can Having the same target photosensitive value facilitates the processing of the biometric feature collection chip, so that the biometric feature collection chip can maintain a set of algorithms and is compatible with soft screens and hard screens at the same time, which is conducive to improving the compatibility and applicability of the biometric feature collection chip.
  • the light-sensing value of the first area may be understood as the light-sensing value collected by the pixels located in the first area.
  • the photosensitivity value of the first area may be: acquiring the photosensitivity value collected by the pixels in the first area that meet the preset condition.
  • Preset conditions can be set according to actual needs, and several forms of preset conditions are described below:
  • the preset condition may be any one of the following: one or more random pixels in the first area, a pixel located in the center of the first area, and all pixels in the first area.
  • the preset condition may be: pixels in the first area that do not belong to bad pixels.
  • the above-mentioned dead pixels can include two categories: one is the bad pixels formed due to the limitation of the process; the other is the pixels set as color filters (Color Filter, CF) above (CF dots for short). These two kinds of dead pixels can be tested in the whole machine testing stage before leaving the factory, and stored in the whole machine, which can be a terminal such as a mobile phone or a tablet computer.
  • pixels with CF may actually only receive red light, or only green light, or only blue light, compared to other pixels without CF, pixels with CF only receive light of a certain band .
  • the pixels with CF set have different light sensitivity, which will cause some interference on the final collected biometric image. Therefore, in this embodiment, the pixels with CF are also regarded as pixels belonging to bad pixels.
  • the configuration parameters include, in addition to the above-mentioned first exposure time length, first area, and target sensitivity value, the following parameters are used to determine the first
  • the reference information of the first type of pixels belonging to the dead pixels in the area then the acquisition of the photosensitive value of the first area mentioned in step 202 may include: according to the reference information, obtaining the first type of pixels in the first area except for the first type of pixels Sensitivity values collected by the second type of pixels. That is to say, the biometric feature collection chip can obtain the photosensitive values collected by the pixels in the first area that do not belong to the dead pixels.
  • the photosensitivity value collected by dead pixels is quite different. Obtaining photosensitivity values collected by pixels not belonging to bad pixels in the first area is beneficial to improve the photosensitivity value of the acquired first region. Accuracy, thereby improving the accuracy of the subsequent determined second exposure duration.
  • the above-mentioned reference information includes: marking information of each pixel in the first area, and the marking information includes: first marking information used to indicate that a pixel belongs to a bad pixel and first marking information used to indicate that a pixel does not belong to a bad pixel. If the second mark information of the points, the biometrics collection chip can determine the first type of pixels belonging to the dead pixels as the pixels marked with the first mark information according to the reference information, and then obtain the second pixels in the first area that do not belong to the bad pixels Sensitivity value collected by class pixels.
  • the first mark information and the second mark information can be set according to actual needs, for example: the first mark information is represented by "0", that is, the first type of pixels belonging to bad pixels are marked as "0", and the second mark information is represented by "0". "1" indicates that normal pixels (also called second-type pixels) that do not belong to bad pixels are marked as "1”, and the schematic diagram of the marking information of each pixel in the first area can refer to FIG. 4 .
  • the configuration parameter of reference information is sent by the software side, the software side can directly send the marking information of each pixel in the first area, which is convenient for the biometric acquisition chip to clearly distinguish whether each pixel is directly based on the marking information of each pixel. It is a bad point.
  • the array shown in Figure 4 can be stored in the biometrics collection chip, which is convenient for the biometrics collection chip to clearly distinguish each pixel directly according to the stored array. Whether it is a bad point.
  • the above-mentioned reference information includes: coordinate information of the bad block area determined based on the first type of pixels belonging to the bad point, and the biometric feature collection chip can determine that the first area belongs to the bad block according to the reference information
  • the first type of pixels is the pixels in the bad block area.
  • the bad block area can be the smallest rectangular area formed by the first type of pixels belonging to bad pixels, so that the coordinate information of the bad block area can be directly represented by the coordinate information of the boundary points of the bad block area, and the data volume of the reference information is relatively smaller.
  • FIG. 5 for a schematic diagram of the bad block area in the first area, and the area framed by a dotted line in FIG. 5 is the bad block area.
  • the bad block area is a regular rectangular area, pixels that are not bad pixels are allowed to exist in the bad block area.
  • the biometric feature acquisition chip can regard the pixels in the bad block area as the first type of pixels belonging to the bad point, and the existence of individual normal pixels in the bad block area will not have a great impact on the subsequent processing.
  • the configuration parameter of reference information is sent by the software side, the software side can directly send the coordinate information of the bad block area, which can reduce the amount of data to be sent and increase the speed of sending.
  • the configuration parameter of the reference information is pre-stored in the biometrics collection chip, the coordinate information of the bad block area can be stored in the biometrics collection chip, which can reduce the amount of stored data and save storage space.
  • step 202 may be: after the biometrics collection chip detects the preset trigger condition, after a preset time interval, the first area is exposed according to the first exposure time, and the photosensitive value of the first area is obtained. Partial exposure after a preset time interval is beneficial to ensure that the biometric feature collection chip can be in a relatively stable state during partial exposure, so that the second exposure time is obtained in a relatively stable state, which improves the acquisition of the second exposure time. The accuracy of the collected biometric images can be improved.
  • the biometric feature acquisition chip is an under-screen fingerprint acquisition chip.
  • the under-screen fingerprint acquisition chip detects that the area where the fingerprint spot on the screen is located is pressed, it can first obtain configuration parameters. After being pressed, the first area is exposed according to the first exposure time after a preset time interval, and the photosensitivity value of the first area is acquired. After the area where the fingerprint spot is located on the screen is pressed, the fingerprint spot starts to light up. After a preset interval, the default fingerprint spot is stable, that is, after the fingerprint spot is stable, the first area is exposed.
  • the under-screen fingerprint collection chip may also start to acquire configuration parameters after a preset period of time after detecting that the area where the fingerprint spot on the screen is located is pressed, and then perform the step of exposing the first area.
  • the second exposure duration required to collect the target photosensitivity value in the photosensitivity area can be determined in combination with the preset relationship.
  • the preset relationship can be the photosensitivity value and the exposure duration.
  • the linear relationship between the exposure time for example, you can refer to the linear relationship between the photosensitive value and the exposure time in Figure 6, combined with the linear relationship, the photosensitive value Rawdata of the first area, the target photosensitive value Target and the first exposure time T1, you can The second exposure duration T2 is obtained through calculation.
  • the biometric feature collection chip can directly capture the photosensitive value of the pixel meeting the preset condition.
  • the collected photosensitivity value is taken as the photosensitivity value of the first area (denoted as Rawdata), and then T2 is calculated according to Rawdata, T1, Target, and the linear relationship shown in FIG. 6 .
  • the biometric feature collection chip can detect the photosensitized value of the multiple pixels meeting the preset condition.
  • the collected photosensitive values are sorted from small to large, and a photosensitive value is selected within a preset range as the photosensitive value of the first area according to the arrangement order of each photosensitive value.
  • T2 is calculated according to the selected photosensitive value, T1, Target, and the linear relationship shown in FIG. 6 .
  • the preset range does not include the photosensitivity values arranged in the first N positions, nor does it include the photosensitivity values arranged in the last N positions, N is an integer greater than 1, and the specific value of N can be set by those skilled in the art according to actual needs , which is not specifically limited in this embodiment.
  • the photosensitivity values arranged in the first N positions and the photosensitivity values arranged in the last N positions may belong to abnormal photosensitivity values, so choosing a photosensitivity value within the preset range as the photosensitivity value of the first area can avoid abnormal
  • the interference of the photosensitivity value on the photosensitivity value of the first region is beneficial to improve the accuracy of the determined photosensitivity value of the first region, thereby improving the accuracy of the calculated T2.
  • the biometric feature collection chip can collect the photosensitivity values collected by the multiple pixels meeting the preset conditions.
  • the light-sensitivity values of the first area are averaged to obtain the average value of the pixels in the first area, and the average value of the pixels is taken as the light-sensitivity value of the first area.
  • T2 is calculated according to the pixel average value, T1, Target, and the linear relationship shown in FIG. 6 . Taking the average value of the photosensitive values collected by multiple pixels as the photosensitive value of the first area reduces the interference caused by inaccurate photosensitive values collected by individual pixels, making the determined photosensitive value of the first area more accurate and reasonable, thereby Improved accuracy of calculated T2.
  • the acquisition of the biometric image can be understood as: the biometric acquisition chip exposes the photosensitive area of the biometric acquisition chip at T2, obtains the photosensitive value of the photosensitive area, and obtains the biometric image based on the photosensitive value. feature image.
  • the biometric feature collection method in this embodiment can be understood as adopting an automatic exposure control (Auto Exposure Control, AEC) method, and the first exposure duration is relatively short, so it can be understood that when it is determined that biometric feature identification or
  • AEC Automatic Exposure Control
  • the biometric feature collection chip is configured to expose the photosensitive area with T2, so as to obtain the biometric feature image.
  • the second exposure time is equivalent to being determined by short-exposure to a local area under the current environment, the second exposure time can adapt to changes in the external environment, thereby improving the adaptability of the biometric feature acquisition chip to the external environment and reducing the exposure time.
  • the impact of changes in the external environment on collection performance is conducive to improving the accuracy of subsequent biometric identification or registration.
  • the configuration parameters also include: filter coefficients; After the photosensitivity value collected by the second type of pixels, it also includes: taking the filling photosensitivity value as the photosensitivity value collected by the first class of pixels; wherein, the filling photosensitivity value is the photosensitivity collected by the second class of pixels around the first class of pixels value; according to the filter coefficient, the light sensitivity value collected by the first type of pixel and the light sensitivity value collected by the second type of pixel are filtered to obtain the filtered light sensitivity value; according to the light sensitivity value of the first area and the first exposure time, it is determined in
  • the second exposure time required for the photosensitive area to collect the target photosensitive value includes: determining the second exposure time required for collecting the target photosensitive value in the photosensitive area according to the filtered photosensitive value and the first exposure time.
  • Step 701 Obtain configuration parameters.
  • Step 702 According to the reference information, determine the first type of pixels belonging to the bad pixels in the first area.
  • Step 703 Expose the first area according to the first exposure time, and acquire the sensitivity values collected by the pixels of the second type except the pixels of the first type in the first area.
  • Step 704 Use the filling sensitivity value as the sensitivity value collected by the first type of pixel; wherein, the filling sensitivity value is the sensitivity value collected by the second type of pixel around the first type of pixel.
  • Step 705 Filter the light-sensing values collected by the first type of pixels and the light-sensing values collected by the second type of pixels according to the filter coefficients to obtain filtered light-sensing values.
  • Step 706 According to the filtered photosensitivity value and the first exposure duration, determine the second exposure duration required to collect the target photosensitivity value in the photosensitivity area.
  • Step 707 Acquire biometric images according to the second exposure time.
  • step 701 is similar to step 201, the main difference is that the configuration parameters in step 701 include, in addition to the first exposure time, the first area, and the target light sensitivity value: used to determine whether the first area belongs to a dead pixel
  • the reference information and filter coefficients of the first type of pixels The reference information has been described above and will not be repeated here.
  • the filter coefficients can be set by those skilled in the art according to actual needs.
  • the biological feature collection chip is arranged under the screen, and the filter coefficient is determined according to the structure of the screen; wherein, the structure of the screen is a soft screen or a hard screen, and the filter coefficient determined based on the hard screen is greater than the filter coefficient determined based on the soft screen .
  • the inventor found through research that: different screen structures have different influences on the photosensitive value collected by pixels, that is, there are differences in the formation of upward burrs on different screen structures in biometric images. Therefore, in this embodiment, according to the structure of the screen The determined filter coefficient is more targeted, and can filter the light-sensing value more reasonably, thereby reducing the influence of different screen structures on the light-sensing value collected by pixels, so as to further improve the accuracy of the determined second exposure duration.
  • the filter coefficient can also be determined according to the structure of the screen and the assembly tolerance of the biometric feature collection chip, and the light-sensing value can be filtered with a more reasonable filter coefficient, thereby minimizing the difference caused by different screen structures and assembly.
  • the influence of the tolerance on the photosensitivity value collected by the pixels so as to further improve the accuracy of the determined second exposure duration.
  • the assembly tolerance is mainly reflected in the error of the object distance P and/or the error of the image distance Q of the lens after the assembly of the biometric feature collection chip and the lens.
  • the difference between the set standard object distances and the error of the image distance Q can be understood as: the difference between the assembled image distance Q and the preset standard image distance.
  • the error of the object distance P and/or the error of the image distance Q is large, the burrs will also be aggravated at this time, and a large filter coefficient is required to filter out the burrs. That is to say, the larger the assembly tolerance, the larger the determined filter coefficient can be, so as to filter out the burr.
  • the filter coefficient may also be dynamically adjusted according to actual needs, so as to achieve a better filter level.
  • the preset standard object distance and the preset standard image distance may be set according to actual needs, which are not specifically limited in this embodiment.
  • the reference information is: the marking information of each pixel in the first area
  • the marking information includes: the first marking information for indicating that the pixel belongs to a bad pixel and the second marking information for indicating that the pixel does not belong to a bad pixel
  • the first type of pixels belonging to bad pixels in the first area determined by the biometrics acquisition chip according to the reference information are: pixels marked with the first marking information.
  • the reference information is the coordinate information of the bad block area determined based on the first type of pixels belonging to the bad point
  • the first type of pixels belonging to the bad point in the first area determined by the biometric acquisition chip according to the reference information is: bad block pixels in the area.
  • the biometric feature collection chip exposes the first area according to the first exposure time, and obtains the light sensitivity values collected by the second type of pixels in the first area except for the first type of pixels, that is, obtains the Sensitive value collected by normal pixels.
  • the biometric feature collection chip can use the photosensitive values collected by the second-type pixels around the first-type pixels to fill the first-type pixels, that is, use the photosensitivity values collected by the normal pixels around the bad pixels to fill the dead point, Set the photosensitivity value collected by the pixel belonging to the dead pixel to the photosensitivity value collected by the normal pixels around the dead pixel.
  • the normal pixels around the dead point may be normal pixels closest to the bad point.
  • the biological feature collection chip filters the light-sensing values collected by the first type of pixels and the light-sensing values collected by the second type of pixels according to the filter coefficients to obtain filtered light-sensing values. That is, the biometric feature collection chip filters the light-sensing values collected by all the pixels in the first area to obtain the filtered light-sensing values.
  • the filtering methods that can be used are: median filtering, Gaussian low-pass filtering, etc. However, this embodiment does not specifically limit this, and other filtering methods can also be used in specific implementations.
  • the photosensitivity values collected by bad pixels are replaced with the photosensitivity values collected by normal pixels around the bad pixels, which facilitates the subsequent direct calculation of the photosensitivity values of all pixels in the first area according to the filter coefficients.
  • the filtered light sensitivity value can better reflect the pixel's true perception of the light signal from the outside world.
  • the second exposure time determined by the photosensitivity value can better adapt to changes in the external environment, thereby making the biometric feature collection chip better adaptable to the external environment, reducing the impact of changes in the external environment on the collection performance, and helping to improve subsequent biometrics. Accuracy of feature recognition or registration.
  • the above-mentioned optical signal from the outside can be understood as the excitation light used for fingerprint collection irradiated on the finger above the screen, and after being scattered, reflected or transmitted by the finger, the formed signal carrying the fingerprint The fingerprint of the information is detected by light.
  • step 706 according to the filtered light-sensing value and the first exposure time, determine the second exposure time required to collect the light-sensing value in the light-sensing area, which may include: filtering the light-sensing value of each pixel in the first area Values are averaged to obtain the average value of the pixels in the first area, and the average value of the pixels is used as the sensitivity value of the first area. Then, T2 is calculated according to the pixel average value, T1, Target, and the linear relationship shown in FIG. 6 .
  • step 706 can refer to FIG. 8 , including:
  • Step 801 Obtain the sensitivity value of the second area.
  • Step 802 Determine the second exposure time required to acquire the target light sensitivity value in the light sensitive area according to the filtered light sensitivity value, the light sensitivity value of the second area and the first exposure time length.
  • the second area is an edge area of the photosensitive area, and the edge area is an area for detecting circuit noise of the biometric feature collection chip, and the second area does not overlap with the first area.
  • Circuit noise can be understood as the noise of the circuit in the biometric feature collection chip, and the circuit in the biometric feature collection chip can include: gain circuit, analog-to-digital conversion circuit, etc.
  • the schematic diagram of the distribution of the first area and the second area in the photosensitive area can refer to FIG. 9 , the photosensitive area 302 in FIG. 902.
  • the first area 301 is located in the non-Dark area 902.
  • the edge area of the photosensitive area of the biometric feature collection chip may be shielded by a shielding material, so it is not easy to perceive external light.
  • the masking material can be metal, that is, the edge area of the photosensitive area is covered by metal, and this part of the area covered by metal can be called the second area, and can also be called Dark area, metal covered area or blackened area. Because the pixels in the second area are covered by metal, they generally cannot receive external light. However, when the strong light is irradiated, the strong light will shine through the metal covering the second area, so that when the strong light is irradiated, the pixels in the second area Pixels may receive some ambient light.
  • the photosensitivity value collected by the pixels in the second area can be understood as: in the current environment, the photosensitivity value collected by the pixel when it is not photosensitive, referred to as the Dark value, so the Dark value can be used to represent the photosensitive
  • the reference value that can be collected can be used to characterize the size of the circuit noise.
  • the photosensitivity value collected by the pixel minus the Dark value can represent: the photosensitivity value actually collected by the pixel after removing the reference, that is, the photosensitivity value actually collected by the pixel after removing the circuit noise.
  • the photosensitive value after removing the reference can eliminate the influence of circuit noise, and can more accurately reflect the light signal from the outside perceived by the pixel.
  • step 801 may be: acquiring light sensitivity values collected by pixels not at the edge of the second area.
  • the inventor found through research that although the pixels in the second area are generally not easy to feel the external light, they are still easily disturbed by the strong light from the outside, especially the possibility that the pixels in the edge area of the second area are disturbed by the strong light bigger. Therefore, in this embodiment, when acquiring the light-sensing value of the second area, the light-sensing value collected by the non-edge pixels in the second area is obtained, so that in the current environment, the determined Dark value can exclude the strong light of the outside world Interference can more accurately reflect the sensitivity value collected by the pixel when it is not sensitive to light, thereby improving the accuracy of the determined second exposure time.
  • step 801 may be: acquiring the photosensitive values collected by the pixels in the middle column a and/or the pixels in the middle row a of the second area, where a is an integer greater than or equal to 1.
  • the second area 901 is distributed around the edges of the photosensitive area 302 , then the second area 901 may include: a sub-area 1 at the left edge of the photo-sensing area 302 , and a sub-area 2 at the right edge of the photo-sensing area 302 , the sub-region 3 at the upper edge of the photosensitive region 302 , and the sub-region 4 at the lower edge of the photosensitive region 302 .
  • the middle a-column pixels and/or the middle a-row pixels of the second area may comprise any one of the following or a combination thereof: the middle a-column pixels of the sub-area 1, the middle a-column pixels of the sub-area 2, and the middle a-rows of the sub-area 3 Pixels, pixels in row a in the middle of sub-region 4.
  • the pixels in column a in the middle of sub-area 1 can be the middle 8 columns of pixels in sub-area 1, in which the 2 columns of the left edge and the right edge of sub-area 1 can be removed from the original 13 columns of pixels 3 columns, so as to leave the middle 8 columns of pixels, and then obtain the Dark value collected by the middle 8 columns of pixels of the sub-area 1.
  • the pixels in the middle a column and/or the middle a row of pixels in the second area are far away from the edge of the second area itself, and the data is relatively concentrated, which can be used to indicate that in the absence of light, while avoiding strong light interference,
  • the reference value that can be collected by the pixel is the accuracy of the Dark value, thereby improving the accuracy of the determined second exposure time.
  • the filtered light-sensing value may be: the filtered light-sensing value corresponding to each pixel in the first area.
  • the filtered light corresponding to each pixel in the first area can be Select one of the light-sensitivity values as Rawdata1, and select one of the light-sensitivity values collected by the pixels in the second area as Dark1, and then calculate T2 according to Rawdata1, Dark1, T1, and Target.
  • T2 can be calculated by the following formula:
  • the selection method of Rawdata1 may be: sort the filtered photosensitive values corresponding to each pixel in the first region from small to large, and select one within a preset range as Rawdata1 according to the arrangement order of each filtered photosensitive value.
  • the preset range does not include the filtered photosensitivity values arranged in the first N positions, nor does it include the filtered photosensitivity values arranged in the last N positions, N is an integer greater than 1, and the specific value of N can be determined by those skilled in the art.
  • the personnel are set according to actual needs, which is not specifically limited in this embodiment. Dark1 can also be selected in a similar manner, and will not be repeated here to avoid repetition.
  • both the photosensitivity value arranged in the first N positions and the filtered photosensitivity value arranged in the last N positions may belong to abnormal photosensitivity values, so selecting one in the preset range as Rawdata1 can avoid going through abnormal photosensitivity values.
  • Calculating T2 is beneficial to improve the accuracy of the determined T2.
  • the process of data processing is relatively simple and has It is beneficial to quickly obtain T2, thereby improving the speed of recognition.
  • step 802 can refer to FIG. 10 , including:
  • Step 1001 Determine the average photosensitive value of the first region according to the filtered photosensitive value.
  • Step 1002 Determine the average light sensitivity value of the second area according to the light sensitivity values collected by the pixels in the second area.
  • Step 1003 According to the average photosensitivity value of the first region, the average photosensitivity value of the second region and the first exposure duration, determine the second exposure duration required to collect the target photosensitivity value in the photosensitive region.
  • the biometric feature collection chip may average the filtered light-sensing values corresponding to each pixel in the first area to obtain the average light-sensing value of the first area.
  • the biometric feature collection chip can also sort the filtered photosensitive values corresponding to each pixel in the first area from small to large, and average the filtered photosensitive values within a preset range to obtain the photosensitive values of the first area. Average light sensitivity.
  • the preset range does not include the filtered photosensitivity values arranged in the first N positions, and also does not include the filtered photosensitivity values arranged in the last N positions, and N is an integer greater than 1.
  • the biometric feature collection chip may average the photosensitive values collected by the pixels in the second area to obtain the average photosensitive value of the second area.
  • the light-sensing values collected by the pixels in the second area may include: light-sensing values collected by the pixels not at the edge of the second area.
  • the light-sensing values collected by the pixels in the second area may include: the light-sensing values collected by the pixels in the middle column a and/or the pixels in the middle row a in the second area.
  • step 1003 the average photosensitive value of the first area is recorded as Rawmean, and the average photosensitive value of the second area is recorded as Darkmean, then the second exposure duration T2 can be calculated by the following formula:
  • the average photosensitive value of the first area can reflect the average level of the photosensitive value of each pixel after filling and filtering of bad pixels
  • the average photosensitive value of the second area can reflect the photosensitive value collected by the pixels in the second area
  • the average level reduces the interference caused by inaccurate photosensitive values collected by individual pixels, which is conducive to improving the accuracy of the calculated T2.
  • the photosensitivity values collected by pixels at the edge of the Dark area can be excluded, which is beneficial to avoid strong light interference from the outside world, and can more accurately reflect the photosensitivity values collected by pixels when they are not photosensitive, thereby further improving the determination The accuracy of the second exposure duration.
  • Both Target and Rawmean use Darkmean for subtraction which is beneficial to eliminate the influence of the structure of the screen itself on the photosensitive value collected by pixels in the current environment, thereby further improving the adaptability of the calculated T2 to the current environment, and making the biometric feature acquisition chip more suitable for the current environment.
  • the adaptability of the environment is better, and the impact of changes in the external environment on the collection performance is reduced, which is conducive to further improving the accuracy of subsequent biometric identification or registration.
  • the configuration parameters mentioned in step 201 or step 701 include, in addition to the first exposure duration, the first area, and the target photosensitive value, the upper limit duration corresponding to the photosensitive area and/or the lower limit corresponding to the photosensitive area Duration, as mentioned in step 204 or step 707, according to the second exposure duration, collecting the biometric image includes: if the configuration parameter also includes the upper limit duration, if the second exposure duration is greater than the upper limit duration, then according to the upper limit duration, Collecting a biometric image; if the configuration parameter also includes a lower limit duration, if the second exposure duration is less than the lower limit duration, the biometric image is collected according to the lower limit duration.
  • T2_max the upper limit duration corresponding to the photosensitive area
  • T2_min the lower limit duration corresponding to the photosensitive area
  • T2_min and T2_max can be set by those skilled in the art according to actual needs, in order to prevent the exposure time used in the final collection of biometric images from being too long or too small, so as to ensure that the final biometric images collected can be relatively clear and easy to identify or register.
  • the biometric image is collected according to the upper limit duration; when the second exposure duration is less than the lower limit duration, the biometric image is collected according to the lower limit duration, It is beneficial to avoid the inaccuracy of the final collected biometric image caused by the calculated second exposure duration under abnormal circumstances may be too small or too large, and ensure that the final collected biometric image can be relatively clear and convenient for identification or registration.
  • the biometric feature collection chip is set in the terminal, and the configuration parameters also include an upper limit duration corresponding to the photosensitive area and a lower limit duration corresponding to the photosensitive area, and the upper limit duration and the lower limit duration satisfy the following relationship:
  • T2_max T0+T0*a1
  • T2_min T0-T0*a2
  • T0 is the default exposure duration of the terminal when it leaves the factory
  • T2_max is the upper limit duration
  • T2_min is the lower limit duration
  • a2 is greater than or equal to a1.
  • a2 and a1 can be set according to actual needs. For example, the value ranges of a1 and a2 are as follows:
  • the default exposure time of the terminal when it leaves the factory may be the default exposure time set based on the result of the calibration of the whole machine when the terminal is in the mass production stage of the whole machine.
  • the inventor found through research that the probability and range of fluctuations in the direction of the second exposure duration exceeding the default exposure duration are small, and the probability and range of fluctuations in the direction lower than the default exposure duration are relatively large. Therefore, a2 is greater than or equal to a1, and there is It is beneficial to adapt to different fluctuation situations that may actually exist in the second exposure duration.
  • the configuration parameters mentioned in step 201 or step 701 further include: a pulse width modulation (Pulse Width Modulation, PWM) dimming cycle of the screen.
  • PWM Pulse Width Modulation
  • collecting the biometric image includes: if the second exposure time is not equal to the integer multiple of the PWM dimming cycle, adjust the second exposure time to an integer of the PWM dimming cycle times, according to the adjusted second exposure time, to collect biometric images.
  • the second exposure duration can be adjusted to an integer multiple of the PWM dimming period by the following formula:
  • T2' (uint8(T2/T2_pwm))*T2_pwm
  • T2' is the adjusted second exposure duration
  • T2 is the second exposure duration determined in step 203 or step 706
  • T2_pwm is the PWM dimming cycle of the screen
  • uint8 represents an unsigned integer data type.
  • the inventor found through research that: for screens with a high drop ratio, when the second exposure time is not equal to an integer multiple of the PWM dimming period, there may be horizontal stripes in the collected biometric image, such as shown in Figure 11
  • the fingerprint image shown is the horizontal stripe image. Therefore, in this embodiment, the second exposure duration is adjusted to an integer of the PWM dimming cycle, and the biometric image is collected with the adjusted second exposure duration, which is beneficial to avoid the biometric collection under the screen with a high drop ratio. Horizontal stripes appear in the biometric image collected by the chip, thereby improving the accuracy of the collected biometric image.
  • the brightness drop of the screen with a high drop ratio type meets any of the following conditions: when PWM dimming is used for dimming, the brightness of the screen drops to 10% of the normal brightness of the screen between two PWM dimming cycles Below; when the DC dimming method is used for dimming, the brightness of the screen between frames drops below 10% of the normal brightness of the screen.
  • the normal brightness of the screen may be set according to actual needs, and the normal brightness of different screens may be different, which is not specifically limited in this embodiment.
  • the PWM dimming period of the screen may be increased in configuration parameters.
  • the implementation of acquiring biometric images can refer to Figure 12, including:
  • Step 1201 Adjust the parameter value of the first parameter, the second parameter and the third parameter according to the second exposure time to obtain the target parameter value of the first parameter, the target parameter value of the second parameter and the target parameter value of the third parameter Target parameter value.
  • Step 1202 Acquire biometric images according to the target parameter value of the first parameter, the target parameter value of the second parameter, and the target parameter value of the third parameter.
  • the first parameter is the duration of the line blanking phase, denoted as H_Blank.
  • H_Blank the duration of the line blanking phase
  • the second parameter is the duration of the vertical blanking phase, denoted as V_Blank.
  • V_Blank A complete image scanning signal is composed of line signal sequences separated by horizontal blanking intervals, called a frame. After the scanning point scans a frame, it needs to return from the lower right corner of the image to the upper left corner of the image to start scanning a new frame. This time interval is called vertical blanking, also known as field blanking.
  • the third parameter is the delay time for starting exposure of each row, which is recorded as V_Delay.
  • the third parameter is how long each row of pixels is delayed to start exposure.
  • the biometric feature collection chip can determine the first scanning duration required for scanning a single row of pixels and the second scanning duration required for scanning a single pixel. Then, according to the first relationship, the parameter value of the first parameter is adjusted to obtain the target parameter value of the first parameter; according to the second relationship, the parameter value of the second parameter and the parameter value of the third parameter are adjusted to obtain the first parameter value The target parameter value for the second parameter and the target parameter value for the third parameter.
  • the target parameter value of the first parameter conforms to the first relationship, and the first relationship is the relationship between the second scanning duration, the number of pixels in each row in the pixel array, the parameter value of the first parameter and the first scanning duration.
  • the target parameter value of the second parameter and the target parameter value of the third parameter conform to the second relationship, the second relationship is the first scan duration, the total number of rows in the pixel array, the parameter value of the second parameter and the parameter value of the third parameter and the first The relationship between the two exposure times.
  • the first scan time required to scan a single row of pixels can be recorded as Row_time, the first-in-first-out queue (First Input First Output, FIFO) storage capacity of the biometric acquisition chip and the serial peripheral interface (Serial Peripheral Interface, SPI). Speed will affect the size of Row_time, SPI speed may limit the minimum value of Row_time.
  • a biometric feature collection chip has a corresponding Row_time, and the Row_time can be obtained from the parameter test of the biometric feature collection chip in the mass production stage, and stored in the biometric feature collection chip.
  • the second scanning duration required for scanning a single pixel can be recorded as 1/pixel_clock, where pixel_clock is a clock period of a pixel.
  • H_Valid The number of pixels in each row in the pixel array is denoted as H_Valid, and the total number of rows in the pixel array is denoted as V_Valid. It can be understood that, for a certain biometric feature collection chip, H_Valid and V_Valid in the biometric feature collection chip can be determined.
  • the first relationship can be expressed as follows:
  • the second relation can be expressed as follows:
  • H_Valid, V_Valid, 1/pixel_clock, Row_time, and T2 are all determined values
  • H_Blank, V_Blank, and V_Delay are three parameter values to be adjusted.
  • H_Blank can be adjusted through the first relationship, so that a target parameter value of the first parameter that conforms to the first relationship is finally obtained, and finally the parameter value that can make the first relationship established is used as the target of the adjusted first parameter parameter value.
  • V_Blank and V_Delay can be adjusted through the second relationship, so that a target parameter value of the second parameter and a target parameter value of the third parameter that conform to the second relationship are finally obtained, and finally the two parameters that can make the second relationship established parameter values as the adjusted target parameter value of the second parameter and the target parameter value of the third parameter. Since there are two parameters V_Blank and V_Delay as variables in the second relationship, one variable can be fixed first, and the other variable can be adjusted. When the adjustment of the other variable can no longer make the calculation result close to T2, the previously fixed variable can be adjusted. , by adjusting the two variables mutually, the two target parameter values that can make the second relationship established are finally adjusted.
  • the configuration parameters further include: the lower limit parameter value of the first parameter, and adjusting the parameter value of the first parameter according to the first relationship to obtain the target parameter value of the first parameter, including: according to the first relationship , in the process of adjusting the parameter value of the first parameter, if the parameter value of the first parameter is adjusted to the lower limit parameter value and still cannot meet the first relationship, the lower limit parameter value is used as the target parameter value of the first parameter.
  • the lower limit parameter value of the first parameter can be recorded as H_Blank_min, and H_Blank_min can be determined based on the minimum value of Row_time.
  • H_Blank_min the target parameter value of the final adjusted first parameter, that is, the first
  • the minimum target parameter value of a parameter is H_Blank_min.
  • the parameter value of the first parameter directly affects the first scanning time Row_time consumed by scanning a single row of pixels, and Row_time will affect the normal output of the photosensitive value. Therefore, setting the lower limit parameter value of the first parameter is beneficial to ensure that the adjustment does not affect Normal output of light sensitivity value.
  • H_Blank in the process of adjusting the parameter values of H_Blank, V_Blank, and V_Delay, H_Blank can also be directly adjusted to H_Blank_min in the configuration parameters, first, V_Delay is fixed to 0, and V_Blank is adjusted until V_Blank cannot be adjusted to make the second After the relationship is established, start to adjust V_Delay.
  • This adjustment is beneficial to reduce the adjustment complexity and speed up the adjustment speed, thereby speeding up the speed of collecting biometric images, so as to speed up the subsequent biometric identification or registration.
  • the target parameter values of these three parameters can be set in the biometrics collection chip, so that the biometrics
  • the acquisition chip acquires the biometric image
  • the final exposure time is T2.
  • the biometric feature collection chip is an off-screen fingerprint collection chip
  • the flow chart of the biometric feature collection method applied to the off-screen fingerprint collection chip can refer to FIG. 13 , including:
  • Step 1301 the software side waits for the fingerprint light spots displayed on the screen to be stable, and sends configuration parameters to the biometric feature collection chip.
  • the software side waits for the fingerprint spot displayed on the screen to be stable, which can be understood as: after the software side determines that the fingerprint spot displayed on the screen is pressed, it waits for a preset time length, and the preset time length is greater than or equal to when the fingerprint spot starts to be lit up to the fingerprint spot The minimum length of time required for stabilization. After the software side waits for a preset period of time, the fingerprint spot is stable by default, and then the software side sends configuration parameters to the biometric feature collection chip.
  • the configuration parameters include: the first exposure duration T1, the first area, the target photosensitive value Target, reference information, filter coefficient, the upper limit duration T2_max corresponding to the photosensitive area, the lower limit duration T2_min corresponding to the photosensitive area, and the lower limit parameter value H_Blank_min of the first parameter. If the screen is a high drop ratio screen, the configuration parameters also include the PWM dimming cycle of the screen.
  • Step 1302 Expose the first area according to the first exposure time to obtain the sensitivity value collected by each pixel in the first area.
  • Step 1303 Remove the pixels of the first type that belong to bad pixels in the pixels in the first area, and use the filling light-sensing value as the light-sensing value collected by the first-type pixels.
  • the collected photosensitivity value and the photosensitivity value collected by the second type of pixels are filtered to obtain the filtered photosensitivity value.
  • the filling light-sensing value is the first light-sensing value collected by the second-type pixels located around the first-type pixels.
  • Step 1304 Determine the average light sensitivity value of the first region according to the filtered light sensitivity value.
  • Step 1305 Determine the average light sensitivity value of the second area according to the light sensitivity values collected by the pixels at the non-edge of the second area.
  • Step 1306 According to the average photosensitivity value of the first area, the average photosensitivity value of the second area and the first exposure time length, determine the second exposure time T2 required to collect the target photosensitivity value in the photosensitive area.
  • Step 1307 If T2>T2_max, collect biometric images according to T2_max.
  • Step 1308 If T2 ⁇ T2_min, collect biometric images according to T2_min.
  • Step 1309 If T2_min ⁇ T2 ⁇ T2_max, collect biometric images according to T2.
  • the off-screen fingerprint collection chip can adjust the three parameters H_Blank, V_Blank and V_Delay according to T2_max.
  • the second relationship utilized in the adjustment can be expressed as follows:
  • the off-screen fingerprint collection chip can adjust the three parameters H_Blank, V_Blank and V_Delay according to T2_min.
  • the second relationship utilized in the adjustment can be expressed as follows:
  • the under-screen fingerprint collection chip can collect biometric images according to the adjusted three parameters. Among them, the minimum of H_Blank can be adjusted to H_Blank_min.
  • the biometric feature collection method applied to the under-screen fingerprint collection chip in this embodiment can improve the adaptability of the under-screen fingerprint collection chip to fingerprint light spots, reduce the impact of fingerprint light spot fluctuations on fingerprint collection performance, and help improve fingerprint identification or registration. the accuracy rate.
  • step division of the above various methods is only for the sake of clarity of description. During implementation, it can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent. ; Adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of the algorithm and process are all within the scope of protection of this patent.
  • the embodiment of the present application also relates to a biological feature collection chip, as shown in Figure 14, including a processing unit 1401 and a storage unit 1402 connected to the processing unit 1401, the storage unit 1402 stores information that can be used by the processing unit An instruction executed by 1401, the instruction is executed by the processing unit 1401, so that the processing unit 1401 can execute the biometric feature collection method in any one of the foregoing embodiments.
  • Embodiments of the present application also relate to a terminal, including a biometric feature collection chip as shown in FIG. 14 .
  • Embodiments of the present application also relate to a computer-readable storage medium storing a computer program.
  • the above method embodiments are implemented when the computer program is executed by the processor.
  • a storage medium includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. .

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Abstract

一种生物特征采集方法、芯片、终端及计算机可读存储介质。上述生物特征采集方法包括：获取配置参数(201)；其中，所述配置参数包括：第一曝光时长、第一区域和目标感光值，所述第一区域为所述生物特征采集芯片的感光区域中的局部区域；根据第一曝光时长对第一区域进行曝光，并获取第一区域的感光值(202)；根据第一区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长(203)；根据第二曝光时长，采集生物特征图像(204)，使得可以提高采集到的生物特征图像的准确性，增加后续进行生物特征识别或注册的准确率。

Description

生物特征采集方法、芯片及计算机可读存储介质 技术领域
本申请实施例涉及生物特征检测技术领域，特别涉及一种生物特征采集方法、芯片及计算机可读存储介质。
背景技术
终端的交互解锁方案中生物识别技术己成为一种新兴的交互技术，其中光学指纹识别技术己成为一种非常方便快捷的指纹识别方案。光学指纹识别技术采用屏幕下隐藏式指纹设计，手指直接按下屏幕上显示的指纹图标区域就能解锁。整机厂商越来越多的手机项目支持光学指纹识别功能，也引入了不同的厂商生产的屏幕，不同厂商生产的屏幕差异性较大。
目前，在整机校准阶段，为整机中的生物特征采集芯片设置有一默认曝光时长，整机出厂后基于该默认曝光时长进行生物特征图像采集时，由于外界环境的变化，容易导致生物特征采集芯片对外界环境的变化的适应性变差，影响采集到的生物特征图像的准确性，降低后续进行生物特征识别或注册的准确率。以手机中的屏下指纹采集芯片为例，指纹光斑的波动，容易导致屏下指纹采集芯片对指纹光斑的适应性变差，影响采集到的指纹图像的准确性，降低后续进行指纹识别或注册的准确率。
发明内容
本申请实施方式的目的在于提供一种生物特征采集方法、芯片及计算机可读存储介质，使得可以提高采集到的生物特征图像的准确性，增加后续进行生物特征识别或注册的准确率。
为解决上述技术问题，本申请的实施方式提供了一种生物特征采集方法，应用于生物特征采集芯片，包括：获取配置参数；其中，所述配置参数包括：第一曝光时长、第一区域和目标感光值，所述第一区域为所述生物特征采集芯片的感光区域中的局部区域；根据所述第一曝光时长对所述第一区域进行曝光，并获取所述第一区域的感光值；根据所述第一区域的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长；根据所述第二曝光时长，采集生物特征图像。
本申请的实施方式还提供了一种生物特征采集芯片，包括：处理单元和与所述处理单元连接的存储单元，所述存储单元存储有可被所述处理单元执行的指令，所述指令被所述处理单元执行，以使所述处理单元能够执行上述的生物特征采集方法。
本申请的实施方式还提供了一种终端，包括上述的生物特征采集芯片。
本申请的实施方式还提供了一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现上述的生物特征采集方法。
本申请的实施方式，在进行生物特征图像采集时，先根据配置参数中的第一曝光时长，对生物特征采集芯片的感光区域中的局部区域(即第一区域)进行局部曝光，得到第一区域的感光值。考虑到，感光值与曝光时长之间具有预设关系，因此，根据第一区域的感光值和第一曝光时长，能够合理且准确的确定在感光区域采集到目标感光值所需的第二曝光时长。也就是说，采集生物特征图像时并不是基于出厂时默认的曝光时长进行采集，而是基于在当前环境下得到的第二曝光时长进行生物特征图像的采集，使得采集到的生物特征图像更加准确。即使外界环境发生变化，即当前环境和确定默认的曝光时长时生物特征采集芯片所处的环境相比，发生了变化，由于第二曝光时长相当于是在当前环境下确定的，使得第二曝光时长可以适应外界环境的变化，从而使得生物特征采集芯片对外界环境的适应性变好，降低外界环境的变化对采集性能的影响，有利于提高后续进行生物特征识别或注册的准确率。而且由于第一区域为 感光区域中的局部区域，因此局部曝光的速度较快，在一定程度上可以加快采集到生物特征图像的速度，从而可以加快后续进行生物特征识别或注册的速度。
附图说明
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。
图1是本申请实施例中提到的指纹光斑的示意图；
图2是本申请实施例中提到的一种生物特征采集方法的流程图；
图3是本申请实施例中提到的第一区域与感光区域的关系示意图；
图4是本申请实施例中提到的第一区域中各像素的标记信息的示意图；
图5是本申请实施例中提到的第一区域中坏块区域的示意图；
图6是本申请实施例中提到的感光值与曝光时长之间的线性关系的示意图；
图7是本申请实施例中提到的另一种生物特征采集方法的流程图；
图8是本申请实施例中提到的步骤706的一种实现方式的流程图；
图9是本申请实施例中提到的感光区域中的第一区域和第二区域的分布示意图；
图10是本申请实施例中提到的步骤802的一种实现方式的流程图；
图11是本申请实施例中提到的横纹图像的示意图；
图12是本申请实施例中提到根据第二曝光时长，采集生物特征图像的一种实现方式的流程图；
图13是本申请实施例中提到应用于屏下指纹采集芯片的生物特征采集方法的流程图；
图14是本申请实施例中提到生物特征采集芯片的结构示意图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请部分实施例进行进一步详细说明。本领域的普通技术人员可以理解，在各实施例中，为了使读者更好地理解本申请而提出了许多技术细节。但是，即使没有这些技术细节和基于以下各实施例的种种变化和修改，也可以实现本申请所要求保护的技术方案。以下各个实施例的划分是为了描述方便，不应对本申请的具体实现方式构成任何限定，各个实施例在不矛盾的前提下可以相互结合相互引用。
随着终端行业的高速发展，生物特征采集技术越来越受到人们重视，屏下生物特征采集技术是将生物特征采集芯片设置于屏幕下方，通过生物特征采集芯片采集外部对象的图像，以便来实现后续的生物特征识别或生物特征注册。其中，生物特征识别可以包括：指纹识别、掌纹识别、虹膜识别、人脸识别等。目前，有机发光二极管(Organic Light-Emitting Diode，OLED)屏幕和液晶显示器(Liquid Crystal Display,LCD)屏幕分别是在手机、平板电脑等终端中应用较为广泛的自发光显示屏幕和非自发光显示屏幕。其中，OLED屏幕属于一种电流型的有机发光器件，其可以通过显示驱动模块来控制每一个显示单元(又称为像素)分别进行独立发光。
以指纹采集为例，即生物特征采集芯片为指纹采集芯片。采用OLED屏幕的终端可以实现屏下光学指纹采集，指纹采集芯片设置在OLED屏幕下方，因此该指纹采集芯片也可以称为屏下指纹采集芯片，OLED屏幕的中的像素可以被利用作为指纹激励光源进行屏幕打光。OLED屏幕中位于指纹检测区域(又称感光区域)的像素被驱动发光从而在指纹检测区域显示一个指纹光斑，其发射的光线作为用于指纹识别的激励光照射到OLED屏幕上方的手指上，并经过手指散射、反射或者透射后，形成携带有手指指纹信息的指纹检测光，该指纹检测光返回到OLED屏幕并透过OLED屏幕传输到下方的指纹采集芯片，指纹采集芯片可以接收该指纹检测光并将指纹检测光转换为相应的电信号，从而实现指纹图像采 集。上述指纹光斑的示意图可以参见图1，当用户需要对终端101进行解锁或者其他指纹验证的时候，只需要将手指按压在位于指纹光斑102所在的区域，便可以实现指纹采集，从而基于采集的指纹图像可以进一步进行指纹匹配验证，以完成指纹识别。
相关技术中，具有屏下指纹采集芯片的终端在整机量产阶段，会基于整机校准的结果设置出厂时的默认曝光时长，该默认的曝光时长被存储在终端中。终端出厂后，用户在使用终端进行指纹注册或指纹识别时，会基于终端中存储的该默认曝光时长，采集得到指纹图像。
本申请的发明人发现，用户在使用终端的过程中，如果指纹光斑出现波动的情况，容易导致指纹识别的准确率较低。其中，指纹光斑的波动可能包括：指纹光斑的亮度波动、色温波动等。指纹光斑出现波动的情况可能包括：由于整机校准阶段的指纹光斑异常导致设置的出厂时的默认曝光时长不准确；用户使用过程中，终端处于切换壁纸、屏幕老化、软件更新等环境。发明人通过研究发现，指纹光斑出现波动的情况导致指纹识别的准确率较低的原因在于：终端在出厂后，被用户使用的过程中，屏下指纹采集芯片依然是基于出厂时设置的默认曝光时长采集指纹图像，并不会在使用过程中再调整默认曝光时长，导致屏下指纹采集芯片对指纹光斑的适应性变差，从而造成指纹识别的准确率较低。
为了解决上述的生物特征采集芯片(比如屏下指纹采集芯片)对外界环境的变化(比如指纹光斑波动)的适应性差，影响采集到的生物特征图像(比如指纹图像)的准确性，本申请实施例提供了一种生物特征采集方法，应用于生物特征采集芯片，包括：获取配置参数；其中，配置参数包括：第一曝光时长、第一区域和目标感光值，第一区域为生物特征采集芯片的感光区域中的局部区域；根据第一曝光时长对第一区域进行曝光，并获取第一区域的感光值；根据第一区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长；根据第二曝光时长，采集生物特征图像。本实施例的应用 场景可以包括：需要进行生物特征图像采集的场景，比如生物特征识别、生物特征注册等。生物特征识别、生物特征注册可以为指纹识别、指纹注册、人脸识别、人脸注册等。当生物特征采集芯片确定需要进行生物特征图像采集时，可以触发本实施例中的生物特征采集的流程，即开始获取配置参数。
本申请实施例中，生物特征采集芯片在进行生物特征图像采集时，先根据配置参数中的第一曝光时长，对生物特征采集芯片的感光区域中的局部区域(即第一区域)进行局部曝光，得到第一区域的感光值。考虑到，感光值与曝光时长之间具有预设关系，因此，根据第一区域的感光值和第一曝光时长，能够合理且准确的确定在感光区域采集到目标感光值所需的第二曝光时长。也就是说，采集生物特征图像时并不是基于出厂时默认的曝光时长进行采集，而是基于在当前环境下得到的第二曝光时长进行生物特征图像的采集，使得采集到的生物特征图像更加准确。即使外界环境发生变化，即当前环境和确定默认的曝光时长时生物特征采集芯片所处的环境相比，发生了变化，由于第二曝光时长相当于是在当前环境下确定的，使得第二曝光时长可以适应外界环境的变化，从而使得生物特征采集芯片对外界环境的适应性变好，降低外界环境的变化对采集性能的影响，有利于提高后续进行生物特征识别或注册的准确率。而且由于第一区域为感光区域中的局部区域，因此局部曝光的速度较快，在一定程度上可以加快采集到生物特征图像的速度，从而可以加快后续进行生物特征识别或注册的速度。
在一个实施例中，生物特征采集芯片为屏下指纹采集芯片，该屏下指纹采集芯片采集的生物特征图像可以用于进行指纹识别或指纹注册。对于包括屏下指纹采集芯片的终端而言，即使在用户实际使用的终端的过程中，终端的屏幕出现指纹光斑波动的情况，由于第二曝光时长相当于是在指纹光斑波动的情况下确定的，使得第二曝光时长可以适应指纹光斑的波动情况，从而使得屏下指纹采集芯片对指纹光斑的适应性变好，降低指纹光斑波动对指纹识别性能的影响，有利于提高指纹识别准确率。在具体实现中，生物特征采集芯片也可以 为虹膜特征采集芯片、掌纹特征采集芯片、人脸特征采集芯片等。
在一个实施例中，生物特征采集方法的流程图可以参考图2，包括：
步骤201：获取配置参数。
步骤202：根据第一曝光时长对第一区域进行曝光，并获取第一区域的感光值。
步骤203：根据第一区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长。
步骤204：根据第二曝光时长，采集生物特征图像。
其中，步骤201中的配置参数包括：第一曝光时长、第一区域和目标感光值，第一区域为生物特征采集芯片的感光区域中的局部区域。配置参数可以由本领域技术人员根据实际需要预先进行设置。
在一个实施例中，步骤201中的获取配置参数，包括：当检测到预设触发条件后，获取配置参数；其中，预设触发条件包括：需要进行生物特征注册和/或需要进行生物特征识别。即，生物特征采集芯片在确定需要进行生物特征注册和/或需要进行生物特征识别，获取配置参数。生物特征采集芯片确定需要进行生物特征注册的方式可以为：生物特征采集芯片接收到用户需要进行生物特征注册的通知信息，该通知信息可以由终端中的处理器发送，其中，处理器可以为终端中的中央处理器(Central Processing Unit，CPU)，微处理器、协处理器等。终端可以为手机、平板电脑等设备。生物特征采集芯片确定需要进行生物特征识别的方式可以为：生物特征采集芯片确定终端需要基于生物特征识别进行解锁、需要基于生物特征识别进行支付等。可选的，预设触发条件还可以包括：生物特征采集芯片检测到被启动，则生物特征采集芯片检测到被启动时，获取配置参数。
在一个实施例中，步骤201中的获取配置参数，包括：当检测到预设触发条件后，获取内部存储的配置参数。其中，配置参数预设好之后，可以被预先存储在生物特征采集芯片中，比如预设好的配置参数可以被写入生物特征采 集芯片的寄存器中。也就是说，生物特征采集芯片可以自行获取配置参数，有利于快速获取配置参数。
在一个实施例中，步骤201中的获取配置参数，包括：接收终端中的应用软件下发的配置参数。由应用软件下发配置参数，生物特征采集芯片无需存储这些配置参数，有利于节省成本和存储空间，而且，方便了根据实际需要通过应用软件修改配置参数，提高了修改配置参数的便捷性。可选的，接收终端中的应用软件(下文中也可以称为软件端)下发的配置参数可以为：当检测到预设触发条件后，接收软件端下发的配置参数。比如，软件端可以在检测到预设触发条件后，向生物特征采集芯片下发配置参数，预设触发条件上文已描述过。此处不再赘述。在具体实现中，生物特征采集芯片在无需采集数据阶段可以处于为休眠状态，当需要进行生物特征采集时，生物特征采集芯片被唤醒，软件端开始下发配置参数。
在一个实施例中，生物特征采集芯片在接收到软件端下发的配置参数后，可以将配置参数存储在寄存器中，当后续再次检测到预设触发条件时，生物特征采集芯片可以直接从生物特征采集芯片中的寄存器中获取配置参数，无需每次都由软件端下发，有利于提高获取配置参数的便捷性。
在一个实施例中，生物特征采集芯片为屏下指纹采集芯片，需要进行生物特征注册和/或需要进行生物特征识别包括：检测到屏幕上的指纹光斑所在的区域被按压，预设时长大于或等于指纹光斑开始被点亮到指纹光斑稳定所需要的最小时长。步骤201中的获取配置参数，包括：当检测到屏幕上的指纹光斑所在的区域被按压后，间隔预设时长再获取配置参数。指纹光斑开始被点亮到指纹光斑稳定所需要的最小时长可以由本领域技术人员根据实际需要测试得到，比如可以设置为40ms至50ms，然而本实施例对此不做具体限定。当检测到屏幕上的指纹光斑所在的区域被按压后可以理解为屏下指纹采集芯片确定当前需要进行指纹识别或指纹注册。通过间隔预设时长后，再获取配置参数，有利于确保屏幕上显示的指纹光斑稳定后，屏下指纹采集芯片再获取配置参数，从而再 基于配置参数进行后续第二曝光时长的计算，使得第二曝光时长为指纹光斑稳定后获取的，提高了获取的第二曝光时长的准确性，从而可以提高采集到的指纹图像的准确性，以提高后续进行指纹识别或指纹注册的准确性。
在一个实施例中，屏下指纹采集芯片可以在检测到指纹光斑所在的区域被按压后，将检测到被按压的信息发送给软件端，软件端在接收到被按压的信息时开始计时，计时达到预设时长后，向屏下指纹采集芯片发送配置参数，使得屏下指纹采集芯片可以在检测到屏幕上的指纹光斑所在的区域被按压后，间隔预设时长获取到配置参数。由软件端下发配置参数，屏下指纹采集芯片无需存储这些配置参数，有利于节省成本和存储空间。而且，通过间隔预设时长后，软件端再向屏下指纹采集芯片发送配置参数，使得第二曝光时长为指纹光斑稳定后获取的，提高了获取的第二曝光时长的准确性，从而可以提高采集到的指纹图像的准确性，以提高后续进行指纹识别或指纹注册的准确性。
在一个实施例中，屏下指纹采集芯片可以在检测到指纹光斑所在的区域被按压时开始计时，计时达到预设时长后，从屏下指纹采集芯片的寄存器中获取寄存器中预先存储的配置参数，使得屏下指纹采集芯片可以在检测到屏幕上的指纹光斑所在的区域被按压后，间隔预设时长获取到配置参数。屏下指纹采集芯片可以在无需与软件端交互的条件下，自行获取配置参数，有利于快速获取配置参数，而且，通过间隔预设时长后，屏下指纹采集芯片再获取配置参数，使得第二曝光时长为指纹光斑稳定后获取的，提高了获取的第二曝光时长的准确性，从而可以提高采集到的指纹图像的准确性，以提高后续进行指纹识别或指纹注册的准确性。
在一个实施例中，第一曝光时长(记为T1)，可以根据生物特征采集芯片的线性度确定，线性度越小，确定的第一曝光时长越小。线性度是描述生物特征采集芯片的一个重要指标，线性度越小，表明线性特性越好，即线性度越准确。线性特性越好，T1可以设置的越短，线性特性越差，T1可以设置的越长。发明人通过研究发现：生物特征采集芯片的线性度会影响在相同曝光时长内， 基于采集的感光值预估的光强的准确性，预估的光强的准确性会进一步影响采集的生物特征图像的准确性。因此，本实施例中根据生物特征采集芯片的线性度确定的第一曝光时长，且线性度越小，确定的第一曝光时长越小，在一定程度上有利于提高采集的生物特征图像的准确性，从而提高后续进行生物特征识别或注册的准确性。
在一个实施例中，第一曝光时长还可以根据生物特征采集芯片的线性度和为了完成指纹识别所预设的标准时长来确定。其中，完成生物特征识别所要求的标准时长也可以称为：关键绩效指标考核时长(Key Performance Indicator time，KPI time)。KPI time可以由本领域技术人员根据实际需要进行设置，比如，对于识别速度要求较高时，该KPI time可以设置的较短，对于识别速度要求较低时，该KPI time可以设置的较长，KPI time的设置可以满足不同识别场景下对识别速度的要求。KPI time越大，T1可以设置的越长，KPI time越小，T1可以设置的越短。最终可以综合考虑KPI time和线性特性，来确定T1的大小，T1大于0毫秒。发明人通过研究发现：第一曝光时长T1的长短会影响KPI time，T1越大对识别速度的影响越大。因此，本实施例中根据KPI time和生物特征采集芯片的线性度确定的第一曝光时长，有利于权衡识别速度和识别准确性，能够在标准时长内完成生物特征识别的同时在一定程度上确保识别的准确性。
在一个实施例中，第一曝光时长大于0毫秒且小于或等于10毫秒。也就是说，第一曝光时长T1的取值范围在0到10毫秒之间，T1取值较小，有利于缩短完成生物特征采集的的时间，从而可以缩短后续进行生物特征识别或注册的时间。在具体实现中，在一定范围内(比如0到10毫秒之间)，T1取值越大，确定的T2也就越准确，从而采集的生物特征图像也就越准确。
在一个实施例中，第一曝光时长T1根据KPI time和生物特征采集芯片的线性度确定，且0ms＜T1≤10ms。也就是说，T1根据KPI time和生物特征采集芯片的线性度在0ms和10ms在0毫秒到10毫秒之间选取一个，有利于在尽 可能加快采集速度的同时，确保不会影响采集的准确性。
在一个实施例中，生物特征采集芯片设置在屏幕下方，第一区域的面积根据屏幕的结构确定，屏幕的结构为软屏或硬屏。基于软屏确定的第一区域的面积大于基于硬屏确定的第一区域的面积。也就是说，软屏较硬屏的第一区域更大。软屏由于中心塌陷，相比于硬屏所取的第一区域的面积更大，软屏中心塌陷使得位于软屏中心的像素所采集的感光值偏小，因此取较大的第一区域，使得可以结合较大的第一区域中的像素所采集的感光值，获取第一区域的感光值，有利于适应于不同屏幕类型对第一区域大小的需求，提高进行局部曝光后所采集的感光值的准确性。
在一个实施例中，可以参考图3，第一区域301的中心为感光区域302的聚光中心303。聚光中心303可以理解为与生物特征采集芯片装配在一起的透镜的中心在感光区域302中的投影点。可以理解的是，生物特征采集芯片与透镜装配的过程中，可能存在装配公差，使得透镜的中心与生物特征采集芯片中的感光区域的中心在垂直方向上并不是完全重合。因此，第一区域301为以感光区域的聚光中心为中心的区域，以聚光中心为中心的第一区域中的各像素采集的感光值较为集中，差异较小，有利于提高获取的第一区域的感光值的准确性。然而，在具体实现中，第一区域的中心也可以直接为感光区域的中心。
在一个实施例中，基于软屏确定的第一区域的面积大于基于硬屏确定的第一区域的面积，且软屏和硬屏中的第一区域的中心均为感光区域的聚光中心，有利于在适应于不同屏幕类型对第一区域大小的需求的同时，进一步提高获取的第一区域的感光值的准确性。
在具体实现中，考虑到第一区域越大，光强检测的越准，但第一区域大到了一定程度，光强检测的准确性就不会再增加，同时第一区域越大，采集到生物特征图像所需的时间越长。因此，可以通过仿真确定第一区域的大小，比如，在仿真的过程中可以逐渐增大第一区域的大小，确定每次增大第一区域后光强检测的准确性和采集到生物特征图像所需的时间，根据光强检测的准确性 和采集到生物特征图像所需的时间，对第一区域取一个折衷的值，使得确定的第一区域既可以确保采集到生物特征图像的时间不会过长，也不会对光强检测的准确性造成太大影响。
在一个实施例中，第一区域中的像素数量为基于生物特征采集芯片的图像读出模式binning确定的需以一个像素的模式读出的像素数量的整数倍。比如，生物特征采集芯片的图像读出模式binning为2*2，即需要以一个像素的模式读出的像素数量为4个，则第一区域中的像素数量为4的整数倍。比如，生物特征采集芯片的图像读出模式binning为4*4，即需要以一个像素的模式读出的像素数量为16个，则第一区域中的像素数量为16的整数倍。第一区域的选择考虑到生物特征采集芯片本身的图像读出模式binning，方便了后续基于binning对第一区域中的像素进行处理，有利于适应生物特征采集芯片本身的图像读出模式，提高图像读出的速度即提高采集生物特征图像的速度。
在一个实施例中，第一区域为矩形区域，比如图3中的矩形区域301，该第一区域可以用图中的A、B这两个点的坐标(x0，y0)(x1，y1)表示。可以理解的是，感光区域302中分布有包括若干像素的像素阵列，像素A处于像素阵列中的第x0行第y0列，像素B处于像素阵列中的第x1行第y1列。如果第一区域这一配置参数由软件端下发，软件端可以直接发送该第一区域的边界点的坐标，比如图3中A、B两个点的坐标，可以减少下发的数据量，提高下发速度。如果第一区域这一配置参数预先存储在生物特征采集芯片中，则生物特征采集芯片中可以存储第一区域的边界点的坐标，可以减少存储的数据量，节省存储空间。
在一个实施例中，第一区域还可以用整个感光区域中的像素的标记信息来表示，比如：将第一区域301中的像素均标记为“X”，将感光区域302中除第一区域301中的像素之外的像素标记为“Y”，整个感光区域中的像素可以表示为由“X”和“Y”组成的阵列，该阵列中的“X”形成的区域即为第一区域301。如果第一区域这一配置参数由软件端下发，软件端可以直接发送上述的由“X” 和“Y”组成的阵列，方便了生物特征采集芯片可以直接根据接收的由“X”和“Y”组成的阵列清晰的分辨出感光区域中第一区域。如果第一区域这一配置参数预先存储在生物特征采集芯片中，则生物特征采集芯片中可以存储上述的由“X”和“Y”组成的阵列，方便了生物特征采集芯片可以直接根据存储的由“X”和“Y”组成的阵列清晰的分辨出感光区域中第一区域。
在一个实施例中，生物特征采集芯片设置在屏幕下方，目标感光值基于屏幕的结构对应的增益值确定，屏幕的结构为软屏或硬屏，软屏对应的增益值大于硬屏对应的增益值。目标感光值记为Target，增益值记为Gain，Gain可以表征信号的放大倍数，Gain和Target具有预设的对应关系，该对应关系可以由本领域技术人员根据实际需要进行设置。在具体实现中，屏幕的增益值Gain可以存储在生物特征采集芯片的寄存器中。本实施例中，考虑到软屏的透光率普遍较硬屏的透光率较低，因此，设置软屏对应的增益值大于硬屏对应的增益值，有利于保证软屏和硬屏能够具有相同的目标感光值，方便生物特征采集芯片的处理，使得生物特征采集芯片可以维护一套算法而同时兼容软屏和硬屏，有利于提高生物特征采集芯片的兼容性和适用性。
在步骤202中，第一区域的感光值可以理解为位于第一区域内的像素采集到的感光值。具体的，第一区域的感光值可以为：获取第一区域中满足预设条件的像素所采集的感光值。预设条件可以根据实际需要进行设置，下面对预设条件的几种形式进行说明：
可选的，预设条件可以为以下任意一个：第一区域中随机的一个或多个像素、位于第一区域的中心的像素、第一区域中的所有像素。
可选的，预设条件可以为：第一区域中不属于坏点的像素。上述坏点可以包括两大类：一种是由于工艺的限制所形成的坏点；另一种为上方设置为彩色滤光片(Color Filter，CF)的像素(简称CF点)。这两种坏点均可以在出厂前的整机测试阶段被测试出来，并存储在整机中，该整机可以为手机、平板电脑等终端。考虑到，设置有CF的像素实际可能只接收红光、或只接收绿光、 或只接收蓝光，相比于其他没有设置CF的像素而言，设置有CF的像素只接收某一波段的光，设置有CF的像素相比于周围其他没有设置CF的像素，感光是有差异的，在最终采集的生物特征图像上会造成一些干扰。因此，本实施例中将设置有CF的像素也视为属于坏点的像素。
在预设条件为：第一区域中不属于坏点的像素的情况下，配置参数除了上述的第一曝光时长、第一区域和目标感光值之外，还包括：用于确定所述第一区域中属于坏点的第一类像素的参考信息，则步骤202中提到的获取第一区域的感光值，可以包括：根据参考信息，获取第一区域中除第一类像素之外的第二类像素所采集的感光值。也就是说，生物特征采集芯片可以获取第一区域中的不属于坏点的像素所采集的感光值。坏点采集的感光值相比于正常的像素采集的感光值差异较大，获取第一区域中的不属于坏点的像素所采集的感光值，有利于提高获取的第一区域的感光值的准确性，从而提高后续确定的第二曝光时长的准确性。
在一个实施例中，上述的参考信息包括：所述第一区域中各像素的标记信息，所述标记信息包括：用于表征像素属于坏点的第一标记信息和用于表征像素不属于坏点的第二标记信息，则生物特征采集芯片可以根据参考信息，确定属于坏点的第一类像素为标记有第一标记信息的像素，然后获取第一区域中的不属于坏点的第二类像素所采集的感光值。其中，第一标记信息和第二标记信息可以根据实际需要进行设置，比如：第一标记信息用“0”表示，即属于坏点的第一类像素标记为“0”，第二标记信息用“1”表示，即不属于坏点的正常像素(也称第二类像素)标记为“1”，第一区域中各像素的标记信息的示意图可以参考图4。其中，如果参考信息这一配置参数由软件端下发，软件端可以直接发送第一区域中各像素的标记信息，方便了生物特征采集芯片可以直接根据各像素的标记信息清晰的分辨各像素是否属于坏点。如果参考信息这一配置参数先存储在生物特征采集芯片中，则生物特征采集芯片中可以存储如图4所示的阵列，方便了生物特征采集芯片可以直接根据存储的阵列清晰的分辨出各 像素是否属于坏点。
在另一个实施例中，上述的参考信息包括：基于属于坏点的第一类像素所确定的坏块区域的坐标信息，则生物特征采集芯片可以根据参考信息，确定第一区域中属于坏点的第一类像素为坏块区域中的像素。其中，坏块区域可以为属于坏点的第一类像素所形成的最小矩形区域，使得坏块区域的坐标信息可以直接用坏块区域的边界点的坐标信息表示，则参考信息的数据量相对较小。比如，第一区域中坏块区域的示意图可以参考图5，图5中虚线框出的区域即为坏块区域。通过图5可以看出的是，由于坏块区域呈现为一个规则的矩形区域，因此坏块区域中允许本身不属于坏点的像素点存在，比如图5中的坏块区域中还存在两个标记为“1”的正常的像素。生物特征采集芯片可以将坏块区域中的像素均视为属于坏点的第一类像素，坏块区域中存在个别正常的像素并不会对后续处理造成太大的影响。其中，如果参考信息这一配置参数由软件端下发，软件端可以直接发送坏块区域的坐标信息，可以减少下发的数据量，提高下发速度。如果参考信息这一配置参数预先存储在生物特征采集芯片中，则生物特征采集芯片中可以存储坏块区域的坐标信息，可以减少存储的数据量，节省存储空间。
在一个实施例中，步骤202可以为：生物特征采集芯片在检测到预设触发条件后，间隔预设时长之后根据第一曝光时长对第一区域进行曝光，并获取第一区域的感光值。通过间隔预设时长后，再局部曝光，有利于确保局部曝光时生物特征采集芯片能够处于相对稳定的状态，使得第二曝光时长为在相对稳定的状态下获取的，提高了获取第二曝光时长的准确性，从而可以提高采集的生物特征图像的准确性。
比如，生物特征采集芯片为屏下指纹采集芯片，屏下指纹采集芯片在检测到屏幕上的指纹光斑所在的区域被按压时，可以先获取配置参数，在检测到屏幕上的指纹光斑所在的区域被按压后，间隔预设时长之后根据第一曝光时长对第一区域进行曝光，并获取第一区域的感光值。屏幕上的指纹光斑所在的区 域被按压后，指纹光斑开始被点亮，间隔预设时长后默认指纹光斑稳定，即在指纹光斑稳定后，再开始对第一区域进行曝光。在具体实现中，屏下指纹采集芯片也可以在检测到屏幕上的指纹光斑所在的区域被按压后，间隔预设时长之后再开始获取配置参数，然后再执行对第一区域进行曝光的步骤。
在步骤203中，考虑到感光值和曝光时长存在预设关系，可以结合该预设关系，确定在感光区域采集到目标感光值所需的第二曝光时长，该预设关系可以为感光值和曝光时长之间的线性关系，比如可以参考图6中感光值和曝光时长之间的线性关系，结合该线性关系、第一区域的感光值Rawdata、目标感光值Target和第一曝光时长T1，可以计算得到第二曝光时长T2。
在一个实施例中，如果步骤202中获取的第一区域的感光值为：满足预设条件的一个像素所采集的感光值，则生物特征采集芯片可以直接将满足预设条件的这一个像素所采集的感光值作为第一区域的感光值(记为Rawdata)，然后，根据Rawdata、T1、Target、以及如图6所示的线性关系，计算得到T2。
在一个实施例中，如果步骤202中获取的第一区域的感光值为：满足预设条件的多个像素所采集的感光值，则生物特征采集芯片可以对满足预设条件的多个像素所采集的感光值从小到大进行排序，根据各感光值的排列顺序，在预设范围内选择一个感光值作为第一区域的感光值。然后，根据选择出的感光值、T1、Target、以及如图6所示的线性关系，计算得到T2。其中，预设范围不包括排列在前N位的感光值，也不包括排列在后N位的感光值，N为大于1的整数，N的具体取值可以由本领域技术人员根据实际需要进行设置，本实施例对此不做具体限定。考虑到排列在前N位的感光值和排列在后N位的感光值均有可能属于异常的感光值，因此在预设范围内选择一个感光值作为第一区域的感光值，可以避免异常的感光值对第一区域的感光值产生的干扰，有利于提高确定的第一区域的感光值的准确性，从而提高了计算得到的T2的准确性。
在一个实施例中，如果步骤202中获取的第一区域的感光值为满足预设条件的多个像素所采集的感光值，则生物特征采集芯片可以对满足预设条件的 多个像素所采集的感光值求平均，得到第一区域的像素平均值，将该像素平均值作为第一区域的感光值。然后，根据该像素平均值、T1、Target、以及如图6所示的线性关系，计算得到T2。将多个像素所采集的感光值的平均值作为第一区域的感光值，降低了由于个别像素采集的感光值不准确带来的干扰，使得确定的第一区域的感光值更加准确合理，从而提高了计算得到的T2的准确性。
在步骤204中，根据第二曝光时长，采集生物特征图像可以理解为：生物特征采集芯片以T2，对生物特征采集芯片的感光区域进行曝光，并获取感光区域的感光值，基于感光值得到生物特征图像。
本实施例中生物特征采集方法可以理解为采用了一种自动曝光控制(Auto Exposure Control，AEC)的方式，第一曝光时长取值较短，因此可以理解为，当确定需要进行生物特征识别或注册时，根据配置参数，自动先对第一区域进行短曝光，并获取第一区域的感光值，然后结合感光值与曝光时长的线性关系，通过线性拟合的方式确定第二曝光时长T2，配置生物特征采集芯片以T2对感光区域曝光，从而获得生物特征图像。由于第二曝光时长相当于是在当前环境下通过对局部区域进行短曝光而确定的，使得第二曝光时长可以适应外界环境的变化，从而使得生物特征采集芯片对外界环境的适应性变好，降低外界环境的变化对采集性能的影响，有利于提高后续进行生物特征识别或注册的准确率。
在一个实施例中，配置参数除了第一曝光时长、第一区域、目标感光值、参考信息之外，还包括：滤波系数；在根据参考信息，获取第一区域中除第一类像素之外的第二类像素所采集的感光值之后，还包括：将填充感光值作为第一类像素所采集的感光值；其中，填充感光值为第一类像素周围的第二类像素所采集的感光值；根据滤波系数对第一类像素所采集的感光值和第二类像素所采集的感光值进行滤波，得到滤波后的感光值；根据第一区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长，包括：根据滤波后的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的 第二曝光时长。该实施例中生物特征采集方法的流程图可以参考图7，包括：
步骤701：获取配置参数。
步骤702：根据参考信息，确定第一区域中属于坏点的第一类像素。
步骤703：根据第一曝光时长对第一区域进行曝光，获取第一区域中除第一类像素之外的第二类像素所采集的感光值。
步骤704：将填充感光值作为第一类像素所采集的感光值；其中，填充感光值为第一类像素周围的第二类像素所采集的感光值。
步骤705：根据滤波系数对第一类像素所采集的感光值和第二类像素所采集的感光值进行滤波，得到滤波后的感光值。
步骤706：根据滤波后的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长。
步骤707：根据第二曝光时长，采集生物特征图像。
其中，步骤701与步骤201类似，主要区别之处在于，步骤701中的配置参数除了第一曝光时长、第一区域、目标感光值之外，还包括：用于确定第一区域中属于坏点的第一类像素的参考信息和滤波系数。参考信息在上文已经阐述过，在此不再赘述，滤波系数可以由本领域技术人员根据实际需要进行设置。
在一个实施方式中，生物特征采集芯片设置在屏幕下方，滤波系数根据屏幕的结构确定；其中，屏幕的结构为软屏或硬屏，基于硬屏确定的滤波系数大于基于软屏确定的滤波系数。发明人通过研究发现：不同的屏幕结构，对像素采集的感光值的影响程度存在差异，即生物特征图像在不同的屏幕结构上形成向上的毛刺存在差异，因此，本实施例中根据屏幕的结构确定的滤波系数更具针对性，能够更加合理的对感光值进行滤波，从而降低由于不同的屏幕结构对像素采集的感光值的影响，以进一步提高确定的第二曝光时长的准确性。
可选的，考虑到生物特征采集芯片在装配时不同的装配公差最终对像素采集的感光值的影响程度也存在差异。因此，本实施例中，还可以根据屏幕的 结构和生物特征采集芯片的装配公差确定滤波系数，能够以更加合理滤波系数的对感光值进行滤波，从而最大程度的降低由于不同的屏幕结构和装配公差对像素采集的感光值的影响，以进一步提高确定的第二曝光时长的准确性。其中，装配公差主要体现在生物特征采集芯片与透镜装配后，透镜的物距P的误差和/或像距Q的误差，物距P的误差可以理解为：装配好之后的物距P与预设的标准物距之间的差值，像距Q的误差可以理解为：装配好之后的像距Q与预设的标准像距之间的差值。当物距P的误差和/或像距Q的误差较大时，此时毛刺也会加重，需要较大的滤波系数才能将毛刺滤除掉。也就是说，装配公差越大，确定的滤波系数可以越大，从而将毛刺滤除掉。在具体实现中，根据实际需要也可以动态调整滤波系数，以达到更好的滤波水平。其中，预设的标准物距和预设的标准像距可以根据实际需要进行设置，本实施例对此不作具体限定。
在步骤702中，如果参考信息为：第一区域中各像素的标记信息，标记信息包括：用于表征像素属于坏点的第一标记信息和用于表征像素不属于坏点的第二标记信息，则生物特征采集芯片根据参考信息，确定的第一区域中属于坏点的第一类像素为：标记有第一标记信息的像素。如果参考信息为基于属于坏点的第一类像素所确定的坏块区域的坐标信息，则生物特征采集芯片根据参考信息，确定的第一区域中属于坏点的第一类像素为：坏块区域中的像素。
在步骤703中，生物特征采集芯片根据第一曝光时长对第一区域进行曝光，获取第一区域中除第一类像素之外的第二类像素所采集的感光值，即获取第一区域中正常像素所采集的感光值。
在步骤704中，生物特征采集芯片可以利用第一类像素周围的第二类像素所采集的感光值去填充第一类像素，即利用坏点周围的正常像素采集的感光值填充该坏点，将属于坏点的像素所采集的感光值设置为坏点周围的正常像素所采集的感光值。其中，坏点周围的正常像素可以为距离该坏点位置最近的正常像素。
在步骤705中，生物特征采集芯片根据滤波系数对第一类像素所采集的 感光值和第二类像素所采集的感光值进行滤波，得到滤波后的感光值。即生物特征采集芯片对第一区域中的所有像素所采集的感光值进行滤波，得到滤波后的感光值。其中，在进行滤波时，可以采用的滤波方式为：中值滤波、高斯低通滤波等，然而，本实施例对此不做具体限定，在具体实现中也可通过其它滤波方式。
本实施例中，将坏点即第一类像素采集的感光值替换为坏点周围的正常像素点所采集的感光值，方便了后续直接根据滤波系数对第一区域中的所有像素的感光值进行整体滤波，避免因去除坏点而不进行填充，直接进行滤波后所造成的感光值的突变，滤波后的感光值更能体现出像素对来自外界的光信号的真实感知，结合滤波后的感光值确定的第二曝光时长，更能适应外界坏境的变化，从而使得生物特征采集芯片对外界环境的适应性变好，降低外界环境的变化对采集性能的影响，有利于提高后续进行生物特征识别或注册的准确率。其中，对于屏下指纹采集而言，上述来自外界的光信号可以理解为用于指纹采集的激励光照射到屏幕上方的手指上，并经过手指散射、反射或者透射后，形成的携带有手指指纹信息的指纹检测光。
在步骤706中，根据滤波后的感光值和第一曝光时长，确定在感光区域采集到所感光值所需的第二曝光时长，可以包括：对第一区域中进行滤波后的各像素的感光值求平均，得到第一区域的像素平均值，将该像素平均值作为第一区域的感光值。然后，根据该像素平均值、T1、Target、以及如图6所示的线性关系，计算得到T2。
在一个实施例中，步骤706的实现方式可以参考图8，包括：
步骤801：获取第二区域的感光值。
步骤802：根据滤波后的感光值、第二区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长。
其中，第二区域为感光区域的边缘区域，边缘区域为用于检测生物特征采集芯片的电路噪声的区域，第二区域与第一区域不重叠。电路噪声可以理解 为生物特征采集芯片中的电路的噪声，生物特征采集芯片中的电路可以包括：增益电路、模数转换电路等。感光区域中的第一区域和第二区域的分布示意图可以参考图9，图9中感光区域302中包括：位于感光区域302四周边缘的第二区域901和被第二区域901包围的非Dark区域902，第一区域301位于非Dark区域902中。
生物特征采集芯片的感光区域的边缘区域可能被遮蔽材料遮蔽，不容易感受到外界光。其中，遮蔽材料可以为金属，即感光区域的边缘区域被金属遮盖，被金属遮盖的这部分区域可以称为第二区域，也可以称为Dark区域、金属遮盖区域或遮黑区域。第二区域中的像素由于被金属遮盖，一般情况下接收不到外界光，但在强光照射时，强光会照穿遮盖第二区域的金属，使得在强光照射时第二区域中的像素可能会接收到一些外界光。第二区域中的像素采集到的感光值可以理解为：在当前环境下，不感光时像素所采集的感光值，简称Dark值，因此Dark值可以用来表示在没有光照的情况下，像素所能采集到的基准值，该基准值可以用于表征电路噪声的大小。在有光照的情况下，像素采集的感光值减去Dark值可以表示：去除基准后像素实际采集到的感光值，即去除电路噪声后像素实际采集到的感光值。去除基准后的感光值可以排除电路噪声的影响，能够更加准确的反映像素所感知到的来自外界的光信号。
在一个实施例中，步骤801可以为：获取第二区域的非边缘处的像素所采集的感光值。发明人通过研究发现，第二区域中的像素虽然一般不容易感受到外界的光，但依然容易受到外界的强光干扰，尤其是第二区域的边缘区域中的像素受到强光干扰的可能性更大。因此，本实施例中，在获取第二区域的感光值时，获取第二区域中非边缘处的像素所采集的感光值，从而使得在当前环境下，确定的Dark值能够排除外界的强光干扰，更能准确的体现不感光时像素所采集的感光值，从而提高确定的第二曝光时长的准确性。
在一个实施例中，步骤801可以为：获取第二区域的中间a列像素和/或中间a行像素所采集的感光值，其中a为大于或等于1的整数。比如可以参考 图9，第二区域901分布在感光区域302的四周边缘，则第二区域901可以包括：处于感光区域302的左边缘的子区域1、处于感光区域302的右边缘的子区域2、处于感光区域302的上边缘的子区域3、处于感光区域302的下边缘的子区域4。第二区域的中间a列像素和/或中间a行像素可以包括以下任意之一或其组合：子区域1的中间a列像素、子区域2的中间a列像素、子区域3的中间a行像素、子区域4的中间a行像素。比如，子区域1中共有13列像素，子区域1的中间a列像素可以为子区域1的中间8列像素，其中原本13列像素中可以去除子区域1的左边缘的2列和右边缘的3列，从而留下中间的8列像素，然后，获取子区域1的中间8列像素所采集的Dark值。第二区域中的中间a列像素和/或中间a行像素离第二区域本身的边缘较远，且数据较集中，在避免强光干扰的同时可以提高用来表示在没有光照的情况下，像素所能采集到的基准值即Dark值的准确性，从而提高确定的第二曝光时长的准确性。
在步骤802中，滤波后的感光值可以为：第一区域中各像素对应的滤波后的感光值。在根据滤波后的感光值、第二区域的感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长时，可以在第一区域中各像素对应的滤波后的感光值中选择一个作为Rawdata1，在第二区域中的像素所采集的感光值中选择一个作为Dark1，然后，根据Rawdata1、Dark1、T1、Target，计算T2。比如，可以通过如下公式计算T2：
Figure PCTCN2021095876-appb-000001
其中，Rawdata1的选择方式可以为：对第一区域中各像素对应的滤波后的感光值从小到大进行排序，根据各滤波后的感光值的排列顺序，在预设范围内选择一个作为Rawdata1。其中，预设范围不包括排列在前N位的滤波后的感光值，也不包括排列在后N位的滤波后的感光值，N为大于1的整数，N的具体取值可以由本领域技术人员根据实际需要进行设置，本实施例对此不做具体限定。Dark1也可以采用类似的方式来选取，为避免重复此处不再赘述。考虑到排 列在前N位的感光值和排列在后N位的滤波后的感光值均有可能属于异常的感光值，因此在预设范围内选择一个作为Rawdata1，可以避免通过异常的感光值去计算T2，有利于提高确定的T2的准确性。本实施例中，计算T2时，由于选择的是第一区域中某一个像素对应的滤波后的感光值Rawdata1，以及第二区域中某一个像素采集的Dark1，因此数据处理的过程较简单，有利于快速得到T2，从而提高识别的速度。
在一个实施例中，步骤802的实现方式可以参考图10，包括：
步骤1001：根据滤波后的感光值，确定第一区域的平均感光值。
步骤1002：根据第二区域中的像素所采集的感光值，确定第二区域的平均感光值。
步骤1003：根据第一区域的平均感光值、第二区域的平均感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长。
在步骤1001中，生物特征采集芯片可以对第一区域中各像素对应的滤波后的感光值求平均，得到第一区域的平均感光值。可选的，生物特征采集芯片还可以对第一区域中各像素对应的滤波后的感光值从小到大进行排序，对处于预设范围内的滤波后的感光值求平均，得到第一区域的平均感光值。其中，预设范围不包括排列在前N位的滤波后的感光值，也不包括排列在后N位的滤波后的感光值，N为大于1的整数。
在步骤1002中，生物特征采集芯片可以对第二区域中的像素所采集的感光值求平均，得到第二区域的平均感光值。其中，第二区域中的像素所采集的感光值可以包括：第二区域的非边缘处的像素所采集的感光值。或者，第二区域中的像素所采集的感光值可以包括：第二区域的中间a列像素和/或中间a行像素所采集的感光值。
在步骤1003，第一区域的平均感光值记为Rawmean，第二区域的平均感光值记为Darkmean，则可以通过如下公式计算第二曝光时长T2：
Figure PCTCN2021095876-appb-000002
本实施例中，第一区域的平均感光值可以体现坏点填充以及滤波后的各像素的感光值的平均水平，第二区域的平均感光值可以体现第二区域中的像素所采集的感光值的平均水平，降低了由于个别像素采集的感光值不准确带来的干扰，有利于提高计算得到的T2的准确性。同时，计算Darkmean时可以排除Dark区域中处于边缘处的像素所采集的感光值，有利于避免外界的强光干扰，更能准确的体现不感光时像素所采集的感光值，从而可以进一步提高确定的第二曝光时长的准确性。Target和Rawmean均采用Darkmean做减法，有利于排除当前环境下屏幕本身的结构对像素采集到的感光值的影响，从而进一步提高计算得到的T2对当前环境的适应性，使得生物特征采集芯片对当前环境的适应性更好好，降低外界环境的变化对采集性能的影响，有利于进一步提高后续进行生物特征识别或注册的准确率。
在一个实施例中，步骤201或步骤701中提到的配置参数除了第一曝光时长、第一区域和目标感光值之外，还包括：感光区域对应的上限时长和/或感光区域对应的下限时长，步骤204或步骤707中提到的的根据第二曝光时长，采集生物特征图像，包括：在配置参数还包括上限时长的情况下，若第二曝光时长大于上限时长，则根据上限时长，采集生物特征图像；在配置参数还包括下限时长的情况下，若第二曝光时长小于下限时长，则根据下限时长，采集生物特征图像。
其中，感光区域对应的上限时长记为T2_max，感光区域对应的下限时长记为T2_min。T2_min和T2_max可以由本领域技术人员根据实际需要进行设置，旨在避免最终采集生物特征图像时所采用的曝光时长过大或过小，从而确保最终采集到的生物特征图像能够相对清晰，方便识别或注册。发明人通过研究发现：在强光环境、室内环境、采图光斑正常点亮等异常情况计算的第二曝光时长可能过小和过大。因此，通过设置上限时长和/或下限时长，在第二曝光时长大于上限时长时，根据上限时长，采集生物特征图像；在第二曝光时长小于下限时长时，根据下限时长，采集生物特征图像，有利于避免异常情况下计 算的第二曝光时长可能过小和过大而造成的最终采集的生物特征图像不准确的情况，确保最终采集到的生物特征图像能够相对清晰，方便识别或注册。
在一个实施例中，生物特征采集芯片设置在终端中，配置参数还包括感光区域对应的上限时长和感光区域对应的下限时长，上限时长和下限时长满足如下关系：
T2_max＝T0+T0*a1
T2_min＝T0-T0*a2
其中，T0为终端出厂时的默认曝光时长，T2_max为上限时长，T2_min为下限时长，a2大于或等于a1。其中，a2和a1可以根据实际需要进行设置，比如a1和a2的取值范围如下：
10％≤a1≤30％，30％≤a2≤50％。
终端出厂时的默认曝光时长可以为终端处于整机量产阶段时，基于整机校准的结果设置的默认曝光时长。发明人通过研究发现：第二曝光时长往超出默认曝光时长的方向波动的概率及幅度较小，往低于默认曝光时长的方向波动的概率及幅度较大，因此，a2大于或等于a1，有利于适应第二曝光时长实际可能存在的不同波动情况。
比如，终端出厂时的默认曝光时长为50ms，则T2_max可以在55ms(50+50*10％＝60ms)到65ms(50+50*30％＝65ms)之间选择。T2_min可以在30ms(50-50*30％＝35ms)到(50-50*50％＝25ms)之间选择。假设，T2_max＝65ms，T2_min＝35ms，若T2大于65ms，则以65ms为曝光时长，采集生物特征图像；若T2小于35ms，则以35ms为曝光时长，采集生物特征图像。
在一个实施例中，步骤201或步骤701中提到的配置参数还包括：屏幕的脉冲宽度调制(Pulse Width Modulation，PWM)调光周期。步骤204或步骤707中提到的根据第二曝光时长，采集生物特征图像，包括：若第二曝光时长不等于PWM调光周期的整数倍，将第二曝光时长调整为PWM调光周期的整数倍，根据调整后的第二曝光时长，采集生物特征图像。
比如，可以通过如下公式将第二曝光时长调整为PWM调光周期的整数倍：
T2’＝(uint8(T2/T2_pwm))*T2_pwm
其中，T2’为调整后的第二曝光时长，T2为步骤203或步骤706中所确定的第二曝光时长，T2_pwm为屏幕的PWM调光周期，uint8表示无符号整数这一种数据类型。
本实施例中，发明人通过研究发现：对于高跌落比类型的屏幕，当第二曝光时长不等于PWM调光周期的整数倍时，采集的生物特征图像可能会存在横纹，比如图11所示的指纹图像为即为横纹图像。因此，本实施例中将第二曝光时长调整为PWM调光周期的整数，以调整后的第二曝光时长，采集生物特征图像，有利于避免设置在高跌落比类型的屏幕下方的生物特征采集芯片采集的生物特征图像出现横纹，从而能够提高采集的生物特征图像的准确性。
其中，高跌落比类型的屏幕的亮度跌落满足如下任意一种条件：采用PWM调光方式进行调光时，在两个PWM调光周期之间屏幕的亮度跌落至该屏幕的正常亮度的10％以下；采用直流调光方式进行调光时，帧和帧之间屏幕的亮度跌落至该屏幕的正常亮度的10％以下。其中，屏幕的正常亮度可以根据实际需要进行设置，不同屏幕的正常亮度可能不同，本实施例对此不作具体限定。在具体实现中，如果终端的屏幕属于高跌落比类型的屏幕，则可以在配置参数中增加屏幕的PWM调光周期。
在一个实施例中，根据第二曝光时长，采集生物特征图像的实现方式可以参考图12，包括：
步骤1201：根据第二曝光时长，调整第一参数的参数值、第二参数参数值和第三参数参数值，得到第一参数的目标参数值、第二参数的目标参数值和第三参数的目标参数值。
步骤1202：根据第一参数的目标参数值、第二参数的目标参数值和第三参数的目标参数值，采集生物特征图像。
第一参数为行消隐阶段的时长，记为H_Blank。在将光信号转换为电信号的扫描过程中，扫描总是从图像的左上角开始，水平向前行进，当扫描点到达图像右侧边缘时，扫描点快速返回左侧，重新开始在第1行的起点下面进行第2行扫描，行与行之间的返回过程称为水平消隐，也称行消隐。
第二参数为场消隐阶段的时长，记为V_Blank。一幅完整的图像扫描信号，由水平消隐间隔分开的行信号序列构成，称为一帧。扫描点扫描完一帧后，要从图像的右下角返回到图像的左上角，开始新一帧的扫描，这一时间间隔，叫做垂直消隐，也称场消隐。
第三参数为对每行开始曝光的延迟时长，记为V_Delay。第三参数即为每一行像素延迟多久时间开始曝光。
在步骤1201中，生物特征采集芯片可以确定扫描单行像素所需要的第一扫描时长和扫描单个像素所需要的第二扫描时长。然后，根据第一关系，对第一参数的参数值进行调整，得到第一参数的目标参数值；根据第二关系，对第二参数的参数值和第三参数的参数值进行调整，得到第二参数的目标参数值和第三参数的目标参数值。其中，第一参数的目标参数值符合第一关系，第一关系为第二扫描时长、像素阵列中每行的像素数量、第一参数的参数值与第一扫描时长之间的关系。第二参数的目标参数值和第三参数的目标参数值符合第二关系，第二关系为第一扫描时长、像素阵列中行的总数、第二参数的参数值和第三参数的参数值与第二曝光时长之间的关系。
扫描单行像素所需要的第一扫描时长可以记为Row_time，生物特征采集芯片的先进先出队列(First Input First Output，FIFO)存储能力和串行外设接口(Serial Peripheral Interface，SPI)。速度会影响Row_time的大小，SPI速度可能会限制Row_time的最小值。一个生物特征采集芯片具有对应的Row_time，Row_time可以为生物特征采集芯片在量产阶段的参数测试中测试得到，并存储在生物特征采集芯片中。
扫描单个像素所需要的第二扫描时长可以记为1/pixel_clock， pixel_clock为像素的时钟周期。pixel_clock可以为生物特征采集芯片在量产阶段的参数测试中测试得到，并存储在生物特征采集芯片中。比如，pixel_clock＝20MHz，1/pixel_clock＝50ns。
像素阵列中每行的像素数量记为H_Valid，像素阵列中行的总数记为V_Valid。可以理解的是，对于一个确定的生物特征采集芯片，该生物特征采集芯片中的H_Valid和V_Valid就可以确定。
第一关系可以表示如下：
Row_time＝(H_Blank+H_Valid)*(1/pixel_clock)
第二关系可以表示如下：
Figure PCTCN2021095876-appb-000003
可以理解的是，上述第一关系和第二关系中H_Valid、V_Valid、1/pixel_clock、Row_time、T2均为确定的值，H_Blank、V_Blank、V_Delay为三个待调整的参数值。
在具体实现中，可以通过第一关系调整H_Blank，使得最终得到一个符合第一关系的第一参数的目标参数值，最后将能够使得第一关系成立的参数值作为调整后的第一参数的目标参数值。
在具体实现中，可以通过第二关系调整V_Blank、V_Delay，使得最终得到一个符合第二关系的第二参数的目标参数值和第三参数的目标参数值，最后将能够使得第二关系成立的两个参数值作为调整后的第二参数的目标参数值和第三参数的目标参数值。由于第二关系中存在两个参数V_Blank、V_Delay为变量，因此可以先固定一个变量，调整另一个变量，当另一个变量的调整已经无法使得计算结果接近于T2，则可以开始调整之前固定的变量，通过相互调整两个变量，最终调整得到能够使得第二关系成立的两个目标参数值。
在一个实施例中，配置参数还包括：第一参数的下限参数值，根据第一关系，对第一参数的参数值进行调整，得到第一参数的目标参数值，包括：在根据第一关系，对第一参数的参数值进行调整的过程中，若第一参数的参数 值被调整至下限参数值时还不能符合第一关系，将下限参数值作为第一参数的目标参数值。其中，第一参数的下限参数值可以记为H_Blank_min，H_Blank_min可以基于Row_time的最小值确定，Row_time的最小值越小，H_Blank_min越小，Row_time的最小值越大，H_Blank_min越大。也就是说，本实施例中，在调整H_Blank的过程中，如果H_Blank已经等于H_Blank_min，还不能让第一关系成立，则可以直接将H_Blank_min作为最终调整后的第一参数的目标参数值，即第一参数的目标参数值最小为H_Blank_min。第一参数的参数值直接影响扫描单行像素所消耗的第一扫描时长Row_time，Row_time会影响到感光值的正常输出，因此，通过设置第一参数的下限参数值有利于确保在调整的同时不影响感光值的正常输出。
在一个实施例中，在调整H_Blank、V_Blank、V_Delay的参数值的过程中，也可以直接将H_Blank调整为配置参数中的H_Blank_min，先将V_Delay固定为0，调整V_Blank，直到调整V_Blank无法使第二关系成立，再开始调整V_Delay，这样调整有利于降低调整复杂度，加快调整速度，从而加快采集生物特征图像的速度，以加快后续进行生物特征识别或注册的速度。
当调整后得到第一参数的目标参数值、第二参数的目标参数值和第三参数的目标参数值后，可以将这三个参数的目标参数值设置在生物特征采集芯片内，使得生物特征采集芯片在采集生物特征图像时最终呈现的曝光时长为T2。
在一个实施例中，生物特征采集芯片为屏下指纹采集芯片，应用于该屏下指纹采集芯片的生物特征采集方法的流程图可以参考图13，包括：
步骤1301：软件端等待屏幕上显示的指纹光斑稳定后，向生物特征采集芯片下发配置参数。
其中，软件端等待屏幕上显示的指纹光斑稳定后可以理解为：软件端确定屏幕上显示的指纹光斑被按压后，等待预设时长，预设时长大于或等于指纹光斑开始被点亮到指纹光斑稳定所需要的最小时长。软件端等待预设时长后默认指纹光斑稳定，则软件端向生物特征采集芯片下发配置参数。
配置参数包括：第一曝光时长T1、第一区域、目标感光值Target、参考信息、滤波系数、感光区域对应的上限时长T2_max，感光区域对应的下限时长T2_min、第一参数的下限参数值H_Blank_min。如果屏幕属于高跌落比屏幕，配置参数还包括屏幕的PWM调光周期。
步骤1302：根据第一曝光时长，对第一区域进行曝光，得到第一区域中各像素所采集的感光值。
步骤1303：去除第一区域中各像素中的属于坏点的第一类像素，将填充感光值作为第一类像素所采集的感光值，根据滤波系数，对第一区域中第一类像素所采集的感光值和第二类像素所采集的感光值进行滤波，得到滤波后的感光值。
其中，填充感光值为位于第一类像素周围的第二类像素所采集的第一感光值。
步骤1304：根据滤波后的感光值，确定第一区域的平均感光值。
步骤1305：根据第二区域的非边缘处的像素采集的感光值，确定第二区域的平均感光值。
步骤1306：根据第一区域的平均感光值、第二区域的平均感光值和第一曝光时长，确定在感光区域采集到目标感光值所需的第二曝光时长T2。
步骤1307：若T2＞T2_max，则根据T2_max，采集生物特征图像。
步骤1308：若T2＜T2_min，则根据T2_min，采集生物特征图像。
步骤1309：若T2_min≤T2≤T2_max，则根据T2，采集生物特征图像。
在步骤1307中，屏下指纹采集芯片可以根据T2_max，调整H_Blank、V_Blank、V_Delay三个参数。调整时利用的第二关系可以表示如下：
Figure PCTCN2021095876-appb-000004
在步骤1308中，屏下指纹采集芯片可以根据T2_min，调整H_Blank、V_Blank、V_Delay三个参数。调整时利用的第二关系可以表示如下：
Figure PCTCN2021095876-appb-000005
最后，屏下指纹采集芯片可以根据调整后的三个参数采集生物特征图像。其中，H_Blank的最小可以调整为H_Blank_min。
本实施例中应用于屏下指纹采集芯片的生物特征采集方法可以使得屏下指纹采集芯片对指纹光斑的适应性变好，降低指纹光斑波动对指纹采集性能的影响，有利于提高指纹识别或注册的准确率。
上面各种方法的步骤划分，只是为了描述清楚，实现时可以合并为一个步骤或者对某些步骤进行拆分，分解为多个步骤，只要包括相同的逻辑关系，都在本专利的保护范围内；对算法中或者流程中添加无关紧要的修改或者引入无关紧要的设计，但不改变其算法和流程的核心设计都在该专利的保护范围内。
本申请的实施例还涉及一种生物特征采集芯片，如图14所示，包括处理单元1401和与所述处理单元1401连接的存储单元1402，所述存储单元1402存储有可被所述处理单元1401执行的指令，所述指令被所述处理单元1401执行，以使所述处理单元1401能够执行上述任意一个实施例中的生物特征采集方法。
本申请的实施例还涉及一种终端，包括如图14所示的生物特征采集芯片。
本申请的实施例还涉及一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
即，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请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、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域的普通技术人员可以理解，上述各实施方式是实现本申请的具体实施例，而在实际应用中，可以在形式上和细节上对其作各种改变，而不偏 离本申请的精神和范围。

Claims (30)

  1. 一种生物特征采集方法，其特征在于，应用于生物特征采集芯片，包括：
    获取配置参数；其中，所述配置参数包括：第一曝光时长、第一区域和目标感光值，所述第一区域为所述生物特征采集芯片的感光区域中的局部区域；
    根据所述第一曝光时长对所述第一区域进行曝光，并获取所述第一区域的感光值；
    根据所述第一区域的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长；
    根据所述第二曝光时长，采集生物特征图像。
  2. 根据权利要求1所述的生物特征采集方法，其特征在于，所述生物特征采集芯片设置在终端中，所述获取配置参数，包括：
    接收所述终端中的应用软件下发的配置参数。
  3. 根据权利要求1或2所述的生物特征采集方法，其特征在于，所述获取配置参数，包括：
    当检测到预设触发条件后，获取配置参数；其中，所述预设触发条件包括：需要进行生物特征注册和/或需要进行生物特征识别。
  4. 根据权利要求3所述的生物特征采集方法，其特征在于，所述根据所述第一曝光时长对所述第一区域进行曝光，并获取所述第一区域的感光值，包括：
    当检测到所述预设触发条件后，间隔预设时长之后根据所述第一曝光时长对所述第一区域进行曝光，并获取所述第一区域的感光值。
  5. 根据权利要求4所述的生物特征采集方法，其特征在于，所述生物特征采集芯片为屏下指纹采集芯片，所述需要进行生物特征注册和/或需要进行生物 特征识别包括：检测到屏幕上的指纹光斑所在的区域被按压，所述预设时长大于或等于所述指纹光斑开始被点亮到所述指纹光斑稳定所需要的最小时长。
  6. 根据权利要求1至5任一项所述的生物特征采集方法，其特征在于，所述配置参数还包括：用于确定所述第一区域中属于坏点的第一类像素的参考信息，所述获取所述第一区域的感光值，包括：
    根据所述参考信息，获取所述第一区域中除所述第一类像素之外的第二类像素所采集的感光值。
  7. 根据权利要求6所述的生物特征采集方法，其特征在于，所述参考信息包括：所述第一区域中各像素的标记信息，所述标记信息包括：用于表征像素属于坏点的第一标记信息和用于表征像素不属于坏点的第二标记信息；或者，
    所述参考信息包括：基于属于坏点的第一类像素所确定的坏块区域的坐标信息。
  8. 根据权利要求6或7所述的生物特征采集方法，其特征在于，所述配置参数还包括：滤波系数；在所述根据所述参考信息，获取所述第一区域中除所述第一类像素之外的第二类像素所采集的感光值之后，还包括：
    将填充感光值作为所述第一类像素所采集的感光值；其中，所述填充感光值为所述第一类像素周围的第二类像素所采集的感光值；
    根据所述滤波系数对所述第一类像素所采集的感光值和所述第二类像素所采集的感光值进行滤波，得到滤波后的感光值；
    所述根据所述第一区域的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长，包括：
    根据所述滤波后的感光值和所述第一曝光时长，确定在所述感光区域采集 到所述目标感光值所需的第二曝光时长。
  9. 根据权利要求8所述的生物特征采集方法，其特征在于，所述根据所述滤波后的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长，包括：
    获取第二区域的感光值；其中，所述第二区域为所述感光区域的边缘区域，所述第二区域与所述第一区域不重叠，所述边缘区域为用于检测所述生物特征采集芯片的电路噪声的区域；
    根据所述滤波后的感光值、所述第二区域的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长。
  10. 根据权利要求9所述的生物特征采集方法，其特征在于，所述获取第二区域的感光值，包括：
    获取第二区域的非边缘处的像素所采集的感光值。
  11. 根据权利要求9所述的生物特征采集方法，其特征在于，所述获取第二区域的感光值，包括：
    获取第二区域的中间a列像素和/或中间a行像素所采集的感光值，其中a为大于或等于1的整数。
  12. 根据权利要求9至11任一项所述的生物特征采集方法，其特征在于，所述根据所述滤波后的感光值、所述第二区域的感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长，包括：
    根据所述滤波后的感光值，确定所述第一区域的平均感光值；
    根据所述第二区域中的像素所采集的感光值，确定所述第二区域的平均感光值；
    根据所述第一区域的平均感光值、所述第二区域的平均感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长。
  13. 根据权利要求12所述的生物特征采集方法，其特征在于，所述根据所述第一区域的平均感光值、所述第二区域的平均感光值和所述第一曝光时长，确定在所述感光区域采集到所述目标感光值所需的第二曝光时长，包括：
    通过如下公式计算所述第二曝光时长：
    Figure PCTCN2021095876-appb-100001
    其中，T2为所述第二曝光时长，T1为所述第一曝光时长，Target为所述目标感光值，Rawmean为所述第一区域的平均感光值，Darkmean为所述第二区域的平均感光值。
  14. 根据权利要求8至13任一项所述的生物特征采集方法，其特征在于，所述生物特征采集芯片设置在屏幕下方，所述滤波系数根据所述屏幕的结构确定；其中，所述屏幕的结构为软屏或硬屏，基于硬屏确定的滤波系数大于基于软屏确定的滤波系数。
  15. 根据权利要求1至14任一项所述的生物特征采集方法，其特征在于，所述配置参数还包括：所述感光区域对应的上限时长和/或所述感光区域对应的下限时长，所述根据所述第二曝光时长，采集生物特征图像，包括：
    在所述配置参数还包括所述上限时长的情况下，若所述第二曝光时长大于所述上限时长，则根据所述上限时长，采集生物特征图像；
    在所述配置参数还包括所述下限时长的情况下，若所述第二曝光时长小于所述下限时长，则根据所述下限时长，采集生物特征图像。
  16. 根据权利要求15所述的生物特征采集方法，其特征在于，所述生物特 征采集芯片设置在终端中，所述配置参数还包括所述感光区域对应的上限时长和所述感光区域对应的下限时长，所述上限时长和所述下限时长满足如下关系：
    T2_max＝T0+T0*a1
    T2_min＝T0-T0*a2
    其中，所述T0为所述终端出厂时的默认曝光时长，所述T2_max为所述上限时长，所述T2_min为所述下限时长，所述a2大于或等于所述a1。
  17. 根据权利要求16所述的生物特征采集方法，其特征在于，所述a1和a2的取值范围如下：
    10％≤a1≤30％，30％≤a2≤50％。
  18. 根据权利要求1至17任一项所述的生物特征采集方法，其特征在于，所述生物特征采集芯片设置在屏幕下方，所述配置参数还包括：所述屏幕的脉冲宽度调制PWM调光周期；
    所述根据所述第二曝光时长，采集生物特征图像，包括：
    若所述第二曝光时长不等于所述PWM调光周期的整数倍，将所述第二曝光时长调整为所述PWM调光周期的整数倍；
    根据调整后的第二曝光时长，采集生物特征图像。
  19. 根据权利要求1至18任一项所述的生物特征采集方法，其特征在于，所述第一曝光时长根据所述生物特征采集芯片的线性度确定，所述线性度越小，确定的所述第一曝光时长越小。
  20. 根据权利要求1至19任一项所述的生物特征采集方法，其特征在于，所述第一曝光时长大于0毫秒且小于或等于10毫秒。
  21. 根据权利要求1至20任一项所述的生物特征采集方法，其特征在于， 所述生物特征采集芯片设置在屏幕下方，所述目标感光值基于所述屏幕的结构对应的增益值确定，所述屏幕的结构为软屏或硬屏，软屏对应的增益值大于硬屏对应的增益值。
  22. 根据权利要求1至21任一项所述的生物特征采集方法，其特征在于，所述生物特征采集芯片设置在屏幕下方，所述第一区域的面积根据所述屏幕的结构确定，所述屏幕的结构为软屏或硬屏，基于软屏确定的第一区域的面积大于基于硬屏确定的第一区域的面积。
  23. 根据权利要求1至22任一项所述的生物特征采集方法，其特征在于，所述第一区域的中心为所述感光区域的聚光中心。
  24. 根据权利要求1至23任一项所述的生物特征采集方法，其特征在于，所述第一区域中的像素数量为基于所述生物特征采集芯片的图像读出模式binning确定的需以一个像素的模式读出的像素数量的整数倍。
  25. 根据权利要求1至24任一项所述的生物特征采集方法，其特征在于，所述生物特征采集芯片包括具有若干像素的像素阵列，所述根据所述第二曝光时长，采集生物特征图像，包括：
    根据所述第二曝光时长，调整第一参数的参数值、第二参数的参数值和第三参数的参数值，得到第一参数的目标参数值、第二参数的目标参数值和第三参数的目标参数值；其中，所述第一参数为行消隐阶段的时长，所述第二参数为场消隐阶段的时长，所述第三参数为对每行像素开始曝光的延迟时长；
    根据所述第一参数的目标参数值、所述第二参数的目标参数值和所述第三参数的目标参数值，采集生物特征图像。
  26. 根据权利要求25所述的生物特征采集方法，其特征在于，所述根据所 述第二曝光时长，调整第一参数的参数值、第二参数的参数值和第三参数的参数值，得到第一参数的目标参数值、第二参数的目标参数值和第三参数的目标参数值，包括：
    确定扫描单行像素所需要的第一扫描时长和扫描单个像素所需要的第二扫描时长；
    根据第一关系，对所述第一参数的参数值进行调整，得到第一参数的目标参数值；其中，
    所述第一参数的目标参数值符合所述第一关系，所述第一关系为：
    Row_time＝(H_Blank+H_Valid)*(1/pixel_clock)
    其中，Row_time为所述第一扫描时长，1/pixel_clock为所述第二扫描时长，H_Blank为所述
    第一参数的参数值，H_Valid为所述像素阵列中每行的像素数量；
    根据第二关系，对所述第二参数的参数值和所述第三参数的参数值进行调整，得到第二参数的目标参数值和第三参数的目标参数值；其中，所述第二参数的目标参数值和第三参数的目标参数值符合所述第二关系，所述第二关系为：
    Figure PCTCN2021095876-appb-100002
    其中，T2为所述第二曝光时长，V_Blank为所述第二参数的参数值，V_Valid为所述像素阵列中行的总数、V_Delay为所述第三参数的参数值。
  27. 根据权利要求26所述的生物特征采集方法，其特征在于，所述配置参数还包括：所述第一参数的下限参数值，所述根据第一关系，对所述第一参数的参数值进行调整，得到第一参数的目标参数值，包括：
    在根据第一关系，对所述第一参数的参数值进行调整的过程中，若所述第 一参数的参数值被调整至所述下限参数值时还不能符合所述第一关系，将所述下限参数值作为所述第一参数的目标参数值。
  28. 一种生物特征采集芯片，其特征在于，包括处理单元和与所述处理单元连接的存储单元，所述存储单元存储有可被所述处理单元执行的指令，所述指令被所述处理单元执行，以使所述处理单元能够执行如权利要求1至27中任一所述的生物特征采集方法。
  29. 一种终端，其特征在于，包括如权利要求28所述的生物特征采集芯片。
  30. 一种计算机可读存储介质，存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现权利要求1至27中任一项所述的生物特征采集方法。
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