WO2022257027A1 - 采集指纹图像的方法、装置和电子设备 - Google Patents

采集指纹图像的方法、装置和电子设备 Download PDF

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Publication number
WO2022257027A1
WO2022257027A1 PCT/CN2021/099016 CN2021099016W WO2022257027A1 WO 2022257027 A1 WO2022257027 A1 WO 2022257027A1 CN 2021099016 W CN2021099016 W CN 2021099016W WO 2022257027 A1 WO2022257027 A1 WO 2022257027A1
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Prior art keywords
exposure time
fingerprint sensor
candidate
images
fingerprint
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PCT/CN2021/099016
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English (en)
French (fr)
Inventor
聂红松
张珂
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深圳市汇顶科技股份有限公司
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Priority to PCT/CN2021/099016 priority Critical patent/WO2022257027A1/zh
Publication of WO2022257027A1 publication Critical patent/WO2022257027A1/zh
Priority to US18/501,163 priority patent/US20240078834A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/13—Sensors therefor
    • G06V40/1318—Sensors therefor using electro-optical elements or layers, e.g. electroluminescent sensing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/13—Sensors therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/141—Control of illumination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/60—Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
    • 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
    • G06V40/1347—Preprocessing; Feature extraction
    • G06V40/1359—Extracting features related to ridge properties; Determining the fingerprint type, e.g. whorl or loop
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/20—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
    • G09G3/22—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources
    • G09G3/30—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources using electroluminescent panels
    • G09G3/32—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2354/00—Aspects of interface with display user

Definitions

  • the embodiments of the present application relate to the field of fingerprint collection, and more specifically, to a method, device and electronic equipment for collecting fingerprint images.
  • the ambient light sensor when it is placed under the display screen of the electronic device, the ambient light sensor needs to detect the light intensity of the ambient light penetrating the display screen. In order to avoid the influence of the screen light on the detection accuracy, the ambient light sensor Needs to work properly when the screen is completely off. In order to improve the accuracy of ambient light detection, the drop amplitude of the display screen during the dark period during the dimming cycle is usually reduced, which affects the collection of fingerprint images by the fingerprint sensor below the display screen and reduces the performance of fingerprint detection .
  • Embodiments of the present application provide a method, device and electronic device for collecting fingerprint images, which can reduce the impact of screen drive and screen refresh on fingerprint detection, thereby improving the performance of fingerprint detection.
  • a method for collecting fingerprint images including:
  • the N candidate exposure times including a first exposure time greater than a preset exposure time, and a first exposure time shorter than the preset exposure time
  • the second exposure time and the preset exposure time, the difference between the first exposure time and the preset exposure time and the difference between the preset exposure time and the second exposure time are all preset steps positive integer multiples of and less than the preset exposure time, N is a positive integer greater than or equal to 3;
  • N values of characteristic parameters corresponding to the N candidate exposure times are determined, and the characteristic parameters are used to characterize the effect of the refresh period of the display screen on all Describe the degree of influence of the fingerprint image collected by the fingerprint sensor;
  • the fingerprint sensor is controlled to collect a fingerprint image.
  • the characteristic parameters include at least one of the following parameters: temporal noise, spatial noise, signal-to-noise ratio, and horizontal stripe intensity.
  • the characteristic parameter includes temporal noise
  • the controlling the fingerprint sensor to acquire at least one frame of image based on each of the N candidate exposure times respectively includes:
  • the fingerprint sensor is controlled to collect M frames of images, M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • the characteristic parameter includes spatial noise
  • the controlling the fingerprint sensor to acquire at least one frame of image based on each candidate exposure time of the N candidate exposure times respectively includes:
  • the fingerprint sensor is controlled to collect M frames of images, M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • the characteristic parameter includes horizontal stripe intensity
  • controlling the fingerprint sensor to acquire at least one frame of image based on each of the N candidate exposure times respectively includes:
  • the first value is a minimum value among the N values.
  • the characteristic parameter includes a signal-to-noise ratio
  • the first value is a maximum value among the N values.
  • the preset step length includes the time difference between the end of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor or the time difference of the start of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor .
  • the at least one frame of images is 5 frames of images.
  • a device for collecting fingerprint images including: a processor, the processor is used for:
  • the N candidate exposure times include a first exposure time greater than a preset exposure time, and a first exposure time shorter than the preset exposure time.
  • the second exposure time of the exposure time and the preset exposure time, the difference between the first exposure time and the preset exposure time and the difference between the preset exposure time and the second exposure time are preset A positive integer multiple of the step size and less than the preset exposure time, N is a positive integer greater than or equal to 3;
  • N values of characteristic parameters corresponding to the N candidate exposure times are determined, and the characteristic parameters are used to characterize the effect of the refresh period of the display screen on all Describe the degree of influence of the fingerprint image collected by the fingerprint sensor;
  • the fingerprint sensor is controlled to collect a fingerprint image.
  • the characteristic parameters include at least one of the following parameters: temporal noise, spatial noise, signal-to-noise ratio, and horizontal stripe intensity.
  • the characteristic parameters include time-domain noise
  • the processor is specifically configured to:
  • the fingerprint sensor is controlled to collect M frames of images, M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • the characteristic parameters include spatial noise
  • the processor is specifically configured to:
  • the fingerprint sensor is controlled to collect M frames of images, M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • the characteristic parameters include horizontal stripe intensity
  • the processor is specifically configured to:
  • the first value is a minimum value among the N values.
  • the characteristic parameter includes a signal-to-noise ratio
  • the first value is a maximum value among the N values.
  • the preset step length includes the time difference between the end of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor or the time difference of the start of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor .
  • the at least one frame of images is 5 frames of images.
  • the device for collecting fingerprint images and the fingerprint sensor are packaged together.
  • an electronic device including a display screen, a fingerprint sensor, and a device for collecting fingerprint images in any implementation manner of the second aspect, wherein the fingerprint sensor is used for below.
  • the preset exposure time as the center, a plurality of candidate exposure times are obtained by using a preset step size, and multiple values of the characteristic parameters corresponding to the multiple candidate exposure times are determined, and by selecting among the multiple values
  • the refresh cycle of the display screen has the least impact on the fingerprint image of the fingerprint sensor, and the corresponding candidate exposure time is determined as the target exposure time, and subsequent fingerprint collection is performed based on the target exposure time.
  • the target exposure time determined by the technical solution of the present application to collect fingerprint images can make the performance of the fingerprint sensor corresponding to a specific display screen optimal, that is to say, the refresh cycle of the display screen can affect the The degree of influence is the least, that is, the horizontal stripes in the fingerprint image are the weakest or there are no horizontal stripes.
  • FIG. 1 is a schematic diagram of a dimming cycle of a display.
  • FIG. 2 is a schematic diagram of exposing each row of pixels by a progressive scanning exposure method.
  • Fig. 3 is a schematic diagram of the principle of generating horizontal stripes.
  • Fig. 4 is a schematic block diagram of a method for collecting a fingerprint image according to an embodiment of the present application.
  • Fig. 5 is a distribution diagram of characteristic parameters of different combinations of fingerprint sensor + display screen.
  • FIG. 6 is a schematic diagram of the positions of horizontal stripes in multiple frames of images.
  • Fig. 7 is a schematic diagram of calculating time-domain noise.
  • Fig. 8 is a schematic diagram of calculating spatial noise.
  • Fig. 9 is a distribution diagram of temporal noise and spatial noise at different exposure times.
  • FIG. 10 is a schematic flowchart of a method for collecting fingerprint images according to an embodiment of the present application.
  • FIG. 11 is a schematic diagram of fingerprint images collected under a set of candidate exposure times obtained based on the method for collecting fingerprint images according to the embodiment of the present application.
  • FIG. 12 is a graph of FRR of the whole machine and a graph of streak noise under a set of candidate exposure times.
  • Fig. 13 is a schematic block diagram of a device for collecting fingerprint images according to an embodiment of the present application.
  • Fig. 14 is another schematic block diagram of the device for collecting fingerprint images according to the embodiment of the present application.
  • Figure 15 is an orientation view of an electronic device according to an embodiment of the application.
  • Fig. 16 is a partial cross-sectional structural diagram of the electronic device shown in Fig. 15 along A-A'.
  • the dimming cycle of a certain type of screen shown in FIG. 1 is also called a drop cycle or a refresh cycle, and a dimming cycle includes a bright period and a dark period.
  • the dimming period T1 4.065ms, that is, the refresh rate of the display screen is 246Hz.
  • the dimming period T1 shown in FIG. Vmin 0.997V.
  • the display screen basically has no light output, and the ambient light sensor is not affected by the light intensity of the display screen, so as to more accurately detect the light intensity of the ambient light where the electronic device is currently located. But at this time, if the user performs fingerprint detection, the light emitted by the display screen needs to be used to expose the pixel array in the fingerprint sensor, then this display mode of the display screen will affect the fingerprint detection.
  • the method for collecting fingerprint images can be applied to fingerprint sensors using various exposure methods, and is especially suitable for fingerprint sensors using a rolling shutter method for exposure.
  • Figure 2 shows the progressive scan exposure process.
  • the pixels in the same row in the pixel array are exposed at the same time, and the pixels in the next row are exposed at the same time after the exposure of the pixels in the row starts for a certain period of time. Next, the pixels in the subsequent rows are sequentially exposed.
  • the time difference between the start times of exposure of two adjacent rows of pixels can usually be equal to the data reading time of one row of pixels, so that the reading times of exposed data of different pixel rows do not overlap. Then, the exposed data of M rows of pixels are processed and spliced to form a complete image.
  • the exposure time of a row of pixels in the pixel array of the fingerprint sensor is, for example, usually more than 30ms, while in current applications the exposure time of the entire pixel array has reached 100ms, and the dimming cycle of the display screen is usually 16.6ms, 8.3ms, 4.1ms etc. It can be seen that the exposure time of a row of pixels or pixel array is often longer than the dimming period of the display screen. When the brightness of the display screen is dimmed, then during the dark period of the dimming cycle, the pixel row cannot receive light, which will cause the data of the pixel row to be too small.
  • the embodiment of the present application provides a method for collecting fingerprint images, which can reduce the impact of screen driving and screen refresh on fingerprint detection, thereby improving the performance of fingerprint detection.
  • Fig. 4 is a schematic block diagram of a method 400 for collecting fingerprint images according to an embodiment of the present application.
  • the method 400 shown in FIG. 4 can be executed by a processor, for example, it can be executed by a main control processor of an electronic device, or a microprocessor in a fingerprint recognition device (also called a fingerprint recognition module, a fingerprint module, or a fingerprint device, etc.).
  • the processor executes, that is to say, the device for executing the method 400 for capturing a fingerprint image of the embodiment of the present application may be packaged with the fingerprint sensor, and the embodiment of the present application does not limit the subject of execution of the method 400 .
  • method 400 may include some or all of the following steps.
  • step S410 the fingerprint sensor is controlled to acquire at least one frame of image based on each candidate exposure time in N candidate exposure times, the N candidate exposure times including a first exposure time greater than a preset exposure time, The second exposure time shorter than the preset exposure time and the preset exposure time, the difference between the first exposure time and the preset exposure time and the difference between the preset exposure time and the second exposure time The difference is a positive integer multiple of the preset step size, and N is a positive integer greater than or equal to 3.
  • the electronic device will use a fixed exposure time to control the fingerprint sensor to collect fingerprint images.
  • a fixed exposure time is stored in the electronic device in advance.
  • the sensor captures a fingerprint image.
  • the called exposure time can be understood as the preset exposure time in this application.
  • N candidate exposure times may be acquired in a certain manner.
  • the N candidate exposure times may at least include a first exposure time, a second exposure time and the preset exposure time, wherein the first exposure time is greater than the preset exposure time, and the second exposure time is less than the preset exposure time,
  • the difference between the first exposure time and the preset exposure time is a positive integer multiple of the preset step size and less than the preset exposure time
  • the difference between the preset exposure time and the second exposure time is also a positive integer multiple of the preset step size And less than the preset exposure time.
  • the preset step size can also be understood as the scan step of the minimum exposure time, that is to say, the first exposure time and the second exposure time can be respectively determined according to the difference between the preset exposure time and the positive integer multiple of the preset step size 2. Exposure time.
  • the N candidate exposure times include A-n*B, etc.,A-2*B,A-B,A,A+B, A+2*B,...,A+n*B, where n*B is smaller than A.
  • the difference between the first exposure time and the preset exposure time is smaller than the preset exposure time and the difference between the preset exposure time and the second exposure time is smaller than the preset exposure time, that is, n*B is less than A .
  • the first exposure time and the second exposure time may be symmetrical about the preset exposure time.
  • the difference between the first exposure time and the preset exposure time is equal to the difference between the preset exposure time and the second exposure time.
  • the first exposure time and the second exposure time are asymmetric about the preset exposure time. That is to say, the difference between the first exposure time and the preset exposure time is not equal to the difference between the preset exposure time and the second exposure time.
  • the first exposure time among the N candidate exposure times is A+2*B
  • the second exposure time among the N candidate exposure times is A-B.
  • multiple medians may also be taken in multiple intervals within 0 to 2 times the preset exposure time.
  • the preset exposure time is 100ms
  • the median between 0-200ms is 100ms
  • the median between 0-100ms is 50ms
  • the median between 100-200ms is 150ms
  • the median between 0-50ms The median between 25ms
  • the median between 50-100ms is 75ms
  • the median between 100-150ms is 125ms
  • the median between 150-200ms is 175ms.
  • the N candidate exposure times may include 25ms, 50ms, 75ms, 100ms, 125ms, 150ms and 175ms.
  • the more intervals are divided and the more candidate exposure times are obtained, the greater the probability of obtaining the optimal exposure time, or the closer the final target exposure time is to the optimal exposure time.
  • the embodiment of the present application does not limit the manner of acquiring the N candidate exposure times.
  • the fingerprint sensor may be controlled to capture at least one frame of images of the fixed object based on each candidate exposure time of the N candidate exposure times.
  • the fixed object may be a test finger, that is, the at least one frame of image is a fingerprint image, and the fixed object It can also be other test objects.
  • the fixed object is a test weight, and the test weight can be made of skin-like material with a smooth surface.
  • the exposure time in the embodiment of the present application may refer to the exposure time of the entire pixel array, that is, the exposure time of one frame of image; it may also refer to the exposure time of one pixel row.
  • N values of characteristic parameters corresponding to the N candidate exposure times may be determined according to the at least one frame of image collected at each exposure time, and the characteristic parameters are used to characterize the display screen The degree of influence of the refresh period on the fingerprint image collected by the fingerprint sensor.
  • the characteristic parameter may include at least one of the following parameters: temporal noise, spatial noise, signal-to-noise ratio, and horizontal stripe intensity.
  • time domain noise is used to represent the size of the noise in the time domain of the image, that is, it is used to characterize the fluctuation of continuous multi-frame image measurement under a single press. The positions where the horizontal stripes appear in different frames of images are different, and the others are the same. When the horizontal stripes appear, the noise in the temporal domain will become larger.
  • Spatial noise can be used to characterize the flatness of the image. That is, it can characterize the actual flatness of the flattened image in the three-dimensional space domain.
  • Signal-to-noise ratio signal amount/noise, wherein, the signal amount may refer to a useful signal amount, and the noise may refer to any kind of noise, for example, it may be spatial domain noise or time domain noise.
  • At least one of temporal noise, spatial noise, signal-to-noise ratio, and horizontal stripe intensity is used as a characteristic parameter, which can accurately characterize the existence of horizontal stripes and map the horizontal stripe intensity, so that the fingerprint image collected under the obtained target exposure time It will be less affected by horizontal stripes, which in turn can improve the performance of fingerprint detection.
  • step S430 the candidate exposure time corresponding to the first value representing the smallest degree of influence among the N values is determined as the target exposure time.
  • the exposure time corresponding to the minimum value among the N values is determined as the target exposure time, that is, the first value is the minimum value; if the characteristic parameter is spatial noise, then Determine the exposure time corresponding to the minimum value of the N values as the target exposure time, that is, the first value is the minimum value; if the characteristic parameter is the intensity of horizontal stripes, then the minimum value of the N values corresponds to The exposure time of is determined as the target exposure time; if the characteristic parameter is the signal-to-noise ratio, then the exposure time corresponding to the maximum value among the N values is determined as the target exposure time.
  • the fingerprint sensor may be controlled to collect fingerprint images based on the target exposure time.
  • the fingerprint sensor can use the Rolling Shutter method for exposure under the target exposure time.
  • the method for collecting fingerprint images in the embodiment of the present application centers on the preset exposure time, adopts the preset step size to obtain multiple candidate exposure times, and determines multiple values of the characteristic parameters corresponding to the multiple candidate exposure times, By selecting the value with the least influence of the refresh period of the display screen on the fingerprint image of the fingerprint sensor among multiple values, and determining the corresponding candidate exposure time as the target exposure time, and then performing subsequent fingerprinting based on the target exposure time collection.
  • Using the target exposure time determined in the embodiment of the present application to collect fingerprint images can optimize the performance of the fingerprint sensor when it corresponds to a specific display screen, that is, it can make the impact of the refresh cycle of the display screen on the fingerprint image of the fingerprint sensor
  • the least degree, that is, the horizontal stripes in the fingerprint image are the weakest or there are no horizontal stripes.
  • Figure 5 shows the distribution of characteristic parameters of different combinations of fingerprint sensor + display.
  • the abscissa represents the exposure time
  • the ordinate represents the noise intensity
  • different curves represent different combinations. In the same combination, horizontal stripes appear, disappear, reappear, and disappear again with the fluctuation of the curve.
  • the offset of the clock is fixed (if it is too fast, it will always be fast, if it is slow, it will always be slow, and the degree of offset is also the same), so you only need to choose the combination of fingerprint sensor + display screen that has no stripes or the most stripes.
  • the exposure time corresponding to the weak point is to find the best exposure time for the fingerprint sensor + display.
  • the characteristic parameter includes temporal noise
  • the controlling the fingerprint sensor to acquire at least one frame of image based on each of the N candidate exposure times respectively includes: based on the For the i-th candidate exposure time among the N candidate exposure times, control the fingerprint sensor to collect M frames of images, where M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • Determining N values of characteristic parameters corresponding to the N candidate exposure times for the at least one frame of images collected under exposure times includes: acquiring pixel values corresponding to the same fingerprint sensor pixel in the M frames of images Standard deviation: according to the average value of the standard deviation corresponding to the P fingerprint sensor pixels, determine the value of the temporal noise corresponding to the ith candidate exposure time, where P is a positive integer greater than 1.
  • the fingerprint sensor can continuously collect 5 frames of images after a single press of the test weight, and calculate the temporal noise based on the data of the 5 frames of images.
  • the positions of the horizontal stripes appearing in the five frames of images are shown in Figure 6. It can be seen from Figure 6 that the horizontal stripes appear at random positions, that is, the horizontal stripes between multiple frames of images are not aligned, and the clocks are shifted. The more, the larger the fringe amplitude and the larger the temporal noise.
  • P i, j1 represents the pixel value of row i and column j of the first frame
  • P i, j2 represents the pixel value of row i and column j of the second frame
  • P i, j3 Indicates the pixel value of row i and column j of frame 3
  • P i,j4 represents the pixel value of row i and column j of frame 4
  • P i,j5 represents row i and column j of frame 1
  • the value of temporal noise obtained at one candidate exposure time can be calculated by the following formula:
  • Tnoise i,j std(P i,j1 ⁇ P i,j5 ) (1)
  • std represents the standard deviation function
  • mean represents the mean function
  • the feature parameter includes spatial noise
  • the controlling the fingerprint sensor to acquire at least one frame of image based on each of the N candidate exposure times respectively includes: based on the For the i-th candidate exposure time among the N candidate exposure times, control the fingerprint sensor to collect M frames of images, where M is a positive integer greater than 1, and i is a positive integer less than or equal to N;
  • Determining N values of characteristic parameters corresponding to the N candidate exposure times for the at least one frame of images collected under exposure times includes: acquiring pixel values corresponding to the same fingerprint sensor pixel in the M frames of images Average value; according to the standard deviation of the average value corresponding to the P fingerprint sensor pixels, determine the value of the spatial noise corresponding to the ith candidate exposure time, where P is a positive integer greater than 1.
  • the fingerprint sensor can continuously collect 5 frames of images after a single press of the test weight, and calculate the spatial noise based on the data of the 5 frames of images.
  • P i, j1 represents the pixel value of row i and column j of the first frame
  • P i, j2 represents the pixel value of row i and column j of the second frame
  • P i, j3 Indicates the pixel value of row i and column j of frame 3
  • P i,j4 represents the pixel value of row i and column j of frame 4
  • P i,j5 represents row i and column j of frame 1
  • the pixel value of column j is the pixel value of row i and column j of the first frame
  • P i, j2 represents the pixel value of row i and column j of the second frame
  • P i, j3 Indicates the pixel value of row i and column j of frame 3
  • P i,j4 represents the pixel value of row
  • the value of spatial noise obtained at one candidate exposure time can be calculated by the following formula:
  • std represents the standard deviation function
  • mean represents the mean function
  • Fig. 9 shows distribution diagrams of temporal noise and spatial noise at different exposure times. Among them, the horizontal axis is time, and the vertical axis is noise intensity. Different curves represent the noise distribution of different fingerprint sensor + display combinations.
  • the P fingerprint sensor pixels may be all pixels of the fingerprint sensor, or may be some pixels.
  • the characteristic parameter includes the intensity of horizontal stripes
  • controlling the fingerprint sensor to capture at least one frame of image based on each candidate exposure time of the N candidate exposure times respectively includes: based on The i-th candidate exposure time among the N candidate exposure times controls the fingerprint sensor to collect Q frame images, Q is a positive integer, and i is a positive integer less than or equal to N;
  • Determining N values of characteristic parameters corresponding to the N candidate exposure times for multiple frames of images collected at a time includes: determining according to the peak-to-peak values of multiple fingerprint sensor pixels in each frame of the Q frame image The value of the horizontal stripe intensity corresponding to the ith candidate exposure time.
  • the peak-to-peak value of the fingerprint sensor pixels in each frame of image can be used to quantify the horizontal stripe intensity.
  • the peak-to-peak value of all fingerprint sensor pixels of each frame of image can be calculated, that is, the difference between the maximum pixel value and the minimum pixel value, and then the average value of the peak-to-peak value of all frames can be calculated.
  • characteristic parameters in the embodiments of the present application should include but not limited to the above examples, as long as it can represent the degree of influence of the refresh period of the display screen on the fingerprint image collected by the fingerprint sensor.
  • the preset step size used to determine the N candidate exposure times may be the time difference between the end of exposure of any two adjacent rows of fingerprint sensor pixels in the fingerprint sensor or the time difference between any adjacent rows of fingerprint sensor pixels in the fingerprint sensor.
  • the preset step length may also be the data reading time of a row of fingerprint sensor pixels.
  • N candidate exposure times may be determined first, and then the fingerprint sensor may be controlled to perform exposure under the N candidate exposure times in sequence; The fingerprint sensor is controlled to perform exposure at the candidate exposure time, and then the next candidate exposure time is determined.
  • the technical solution of the embodiment of the present application can be used to select the target exposure time at regular intervals, so that the horizontal stripes can be minimized or eliminated as much as possible to improve the performance of fingerprint recognition .
  • Fig. 10 shows a schematic flowchart of the method for collecting fingerprint images according to the embodiment of the present application. As shown in Figure 10, the method mainly includes:
  • S1300 determine A as the center, and sequentially determine multiple candidate exposure times in steps of multiples of B, for example, A-2B, A-B, A, A+B, and A+2B;
  • S1500 calculating the value of the characteristic parameter corresponding to each candidate exposure time, and marking and sorting the values of the characteristic parameter corresponding to multiple candidate exposure times, for example, A-2B, A-B, A, A+B and A+2B
  • the values of the corresponding characteristic parameters are respectively C1, C2, C3, C4 and C5;
  • the optimal characteristic parameter value refers to the exposure time when the horizontal stripes are the weakest or there are no horizontal stripes.
  • the optimal value of the characteristic parameter refers to the minimum value among the values of the plurality of characteristic parameters calculated in S1500.
  • the optimal characteristic parameter value refers to the maximum value among the values of the plurality of characteristic parameters calculated in S1500. For example, if the value of the optimal characteristic parameter is C2, then its corresponding candidate exposure time A-B is the target exposure time.
  • FIG. 11 is a fingerprint image collected under a group of candidate exposure times obtained based on the technical solution of the embodiment of the present application.
  • the central value of the exposure time is 100ms, that is to say, the preset exposure time is 100ms.
  • Table 1 shows the corresponding relationship between the group of exposure times and the fringe noise value, wherein the fringe noise value may be a temporal noise value, a spatial noise value, a fringe intensity value or other noise values.
  • candidate exposure time 98.4ms 98.8ms 99.2ms 99.6ms 100ms fringe noise value 7.4378 9.2556 9.1282 7.4463 4.4589 candidate exposure time 100.4ms 100.8ms 101.2ms 101.6ms the fringe noise value 4.4279 4.1885 7.5644 9.1670 the
  • the exposure time 100.8ms corresponding to the minimum value of 4.1885 can be considered as the optimal exposure time among the 9 candidate exposure times shown in Table 1, and the optimal exposure time can be determined as the target exposure time.
  • Fig. 12 shows the graph of the false rejection rate (False Reject Rate, FRR) of the whole machine under the above-mentioned set of candidate exposure times and the graph of fringe noise. From the results in the figure, the exposure time corresponding to the minimum streak noise value is selected as the target exposure time. The lower the FRR, the lower the performance and the higher the success rate of unlocking. That is to say, select the exposure with the smaller streak noise value. Time, the more excellent overall performance can be obtained.
  • FRR False Reject Rate
  • the method for collecting fingerprint images according to the embodiment of the present application has been described in detail above.
  • the device for collecting fingerprint images according to the embodiment of the present application will be described below in conjunction with FIG. 13 .
  • the technical features described in the method embodiment are applicable to the following device embodiments .
  • FIG. 13 shows a schematic block diagram of an apparatus 1300 for collecting fingerprint images according to an embodiment of the present application.
  • the device 1300 includes:
  • a control unit 1310 configured to control the fingerprint sensor to capture at least one frame of image based on each of the N candidate exposure times, the N candidate exposure times including a first exposure time greater than a preset exposure time , a second exposure time shorter than the preset exposure time and the preset exposure time, the difference between the first exposure time and the preset exposure time, and the preset exposure time and the second exposure time
  • the difference is a positive integer multiple of the preset step size and less than the preset exposure time, and N is a positive integer greater than or equal to 3;
  • a determining unit 1320 configured to determine N values of characteristic parameters corresponding to the N candidate exposure times according to the at least one frame of image collected at each exposure time, the characteristic parameters being used to characterize the display The degree of influence of the refresh cycle of the screen on the fingerprint image collected by the fingerprint sensor, and
  • the control unit 1310 is also used for:
  • the fingerprint sensor is controlled to collect a fingerprint image.
  • the characteristic parameters include at least one of the following parameters: temporal noise, spatial noise, signal-to-noise ratio, and horizontal stripe intensity.
  • the characteristic parameters include temporal noise
  • the processor 1310 is specifically configured to: control the fingerprint based on the ith candidate exposure time among the N candidate exposure times.
  • the sensor collects M frames of images, where M is a positive integer greater than 1, and i is a positive integer less than or equal to N; obtain the standard deviation of the pixel values corresponding to the same fingerprint sensor pixel in the M frame of images; Corresponding to the average value of the standard deviation, determine the value of temporal noise corresponding to the ith candidate exposure time, where P is a positive integer greater than 1.
  • the characteristic parameters include spatial noise
  • the processor 1310 is specifically configured to: control the fingerprint sensor based on the ith candidate exposure time among the N candidate exposure times.
  • M is a positive integer greater than 1
  • i is a positive integer less than or equal to N
  • P is a positive integer greater than 1.
  • the characteristic parameters include the intensity of horizontal stripes
  • the processor 1310 is specifically configured to: based on the ith candidate exposure time among the N candidate exposure times, control the fingerprint
  • the sensor collects Q frames of images, Q is a positive integer, and i is a positive integer less than or equal to N; according to the peak-to-peak values of multiple fingerprint sensor pixels in each frame of the Q frame of images, determine the ith candidate exposure The value of the horizontal stripe intensity corresponding to the time.
  • the first value is a minimum value among the N values.
  • the characteristic parameter includes a signal-to-noise ratio
  • the first value is a maximum value among the N values.
  • the preset step size includes the time difference between the end of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor or the start of exposure of pixels of two adjacent rows of fingerprint sensors in the fingerprint sensor time difference.
  • the at least one frame of images is 5 frames of images.
  • the device and the fingerprint sensor are packaged together.
  • FIG. 14 shows a schematic structural diagram of another device 1400 for collecting fingerprint images according to an embodiment of the present application.
  • the device 1400 for collecting fingerprint images shown in FIG. 14 includes a processor 1410, and the processor 1410 can call and run a computer program from a memory, so as to implement the method in the embodiment of the present application.
  • the device 1400 for capturing fingerprint images may further include a memory 1420 .
  • the processor 1410 can invoke and run a computer program from the memory 1420, so as to implement the method in the embodiment of the present application.
  • the memory 1420 may be an independent device independent of the processor 1410 , or may be integrated in the processor 1410 .
  • the device 1400 for collecting fingerprint images can specifically be the device 1300 for collecting fingerprint images in the embodiment of the present application, and the device 1400 for collecting fingerprint images can implement the method of collecting fingerprint images in the various methods of the embodiments of the application.
  • the corresponding process implemented by 1300 will not be repeated here.
  • the embodiment of the present application also provides a chip, the chip includes a processor, and the processor can call and run a computer program from the memory, so as to implement the method in the embodiment of the present application.
  • the chip can be applied to the device for collecting fingerprint images in the embodiments of the present application, and the chip can implement the corresponding processes implemented by the device for collecting fingerprint images in the various methods of the embodiments of the present application.
  • the chip can implement the corresponding processes implemented by the device for collecting fingerprint images in the various methods of the embodiments of the present application. For the sake of brevity, here No longer.
  • the chip mentioned in the embodiment of the present application may also be called a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip.
  • the embodiment of the present application further provides a computer-readable medium, which is used to store a computer program, so as to implement the method in the embodiment of the present application.
  • the embodiment of the present application also provides an electronic device, including a display screen, a fingerprint sensor, and any one of the above devices for collecting fingerprint images.
  • the fingerprint sensor is used to be arranged under the display screen.
  • Figure 15 and Figure 16 show schematic diagrams of an electronic device 10 to which the under-screen fingerprint recognition technology can be applied, wherein Figure 15 is a schematic front view of the electronic device 10, and Figure 16 is a schematic diagram of the electronic device 10 shown in Figure 15 along AA' Partial cross-sectional schematic diagram.
  • the electronic device 10 includes a display screen 120, an ambient light sensor disposed below the display screen 120, and a fingerprint sensor 900.
  • the electronic device 10 also includes any of the above-mentioned devices for collecting fingerprint images, wherein the device for collecting fingerprint images can be used with
  • the fingerprint sensor 900 is packaged together, or the device for collecting fingerprint images is a processor independent of the fingerprint sensor 900, for example, a main control processor of an electronic device.
  • the fingerprint sensor 900 includes a light detection part 910 and an optical path guiding structure 903 .
  • the light path guiding structure 903 is disposed above the light detection part 910 .
  • the light detection section 910 includes a pixel array 901 composed of a plurality of pixels 9011, a control circuit 902 connected to the pixel array 901, and the like.
  • the area where the pixel array 901 is located or its sensing area is the fingerprint detection area 103 of the fingerprint sensor 900 .
  • the light path guiding structure 903 is used to guide the light signal returned by the finger on the fingerprint detection area 103 to the pixel array 901 .
  • the light path guiding structure 903 may include a microlens array composed of a plurality of microlenses. Further, there may be at least one light-blocking layer under the microlens array, wherein each light-blocking layer is provided with a plurality of openings respectively corresponding to the plurality of microlenses, and the pixel array 901 includes A plurality of pixels 9011 corresponding to the microlens. Each microlens is used to converge the light signal returned by the finger to the corresponding opening in each light blocking layer, so that the light signal sequentially passes through the corresponding opening in each light blocking layer and is transmitted to the corresponding pixel array 901. Pixel 9011.
  • the optical path guiding structure 903 may include a collimator layer fabricated on a semiconductor silicon wafer, which has a plurality of collimating units or microhole arrays, and the collimating units may be small holes.
  • the optical path guiding structure 903 may include an optical lens layer, which has one or more lens units, and the lens unit may be a lens group composed of one or more aspheric lenses.
  • the light path guiding structure may include a lens 9031 . The light emitted by the light-emitting layer 1201 in the display screen irradiates the finger and the light returned by the finger can be converged to the pixel array 901 of the optical fingerprint sensor through the lens 9031 .
  • the display screen 120 When performing fingerprint detection, the display screen 120 emits a beam of light 111 to the finger 140 above the fingerprint detection area 103 , and the light 111 is reflected on the surface of the finger 140 to form reflected light or scattered inside the finger 140 to form scattered light. Since the ridges (ridges) 141 and valleys (valleys) 142 of the fingerprint have different light reflection capabilities, the reflected light 151 from the fingerprint ridges and the reflected light 152 from the fingerprint valleys have different light intensities, and the reflected light passes through the light path guiding structure. After 903, it is received by the pixel array 901 and converted into a corresponding electrical signal, that is, a fingerprint detection signal. The data of the fingerprint image can be obtained based on the fingerprint detection signal, and further used for fingerprint matching and verification, so as to realize the function of optical fingerprint detection in the electronic device 10 .
  • the electronic device 10 may also include an excitation light source for fingerprint detection.
  • the display screen 120 may be a display screen having a self-luminous display unit, such as an organic light-emitting diode (Organic Light-Emitting Diode, OLED) display screen or a micro-light-emitting diode (Micro-LED) display screen.
  • OLED Organic Light-Emitting Diode
  • Micro-LED micro-light-emitting diode
  • the fingerprint sensor 900 may use the display unit located in the fingerprint detection area 103 of the OLED display screen 120 as an excitation light source for optical fingerprint detection.
  • the electronic device in the embodiment of the present application may be a portable or mobile computing device such as a terminal device, a mobile phone, a tablet computer, a notebook computer, a desktop computer, a game device, a vehicle electronic device, or a wearable smart device, and Electronic databases, automobiles, bank ATMs (Automated Teller Machines, ATMs) and other electronic equipment.
  • the wearable smart devices include full-featured, large-sized devices that can achieve complete or partial functions without relying on smart phones, such as smart watches or smart glasses, and devices that only focus on a certain type of application functions and need to be integrated with other devices such as smart phones.
  • Cooperating equipment such as various smart bracelets, smart jewelry and other equipment for physical sign monitoring.
  • the disclosed systems, devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc and other media that can store program codes. .

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Abstract

一种采集指纹图像的方法、装置和电子设备，所述方法包括：分别基于N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像；根据在所述每个曝光时间下采集的至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度（S420）；将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间（S430）；基于所述目标曝光时间，控制所述指纹传感器采集指纹图像（S440）。所述方法、装置和电子设备，能够降低屏幕驱动和屏幕刷新对指纹检测的影响，从而提高指纹检测的性能。

Description

采集指纹图像的方法、装置和电子设备 技术领域
本申请实施例涉及指纹采集领域，并且更具体地，涉及一种采集指纹图像的方法、装置和电子设备。
背景技术
随着主流市场对全面屏的需求越来越强烈，需要将较多的正面器件移到屏幕下方，例如接近感应传感器和环境光传感器等。对于环境光传感器而言，将其设置在电子设备的显示屏下方时，环境光传感器需要检测穿透显示屏的环境光的光强，为了避免屏幕光对检测准确性的影响，该环境光传感器需要在屏幕完全关闭的时候才能正常工作。为了提升环境光检测的准确性，通常会降低显示屏在调光周期内处于暗时段的跌落幅值，这就影响了显示屏的下方的指纹传感器对指纹图像的采集，降低了指纹检测的性能。
发明内容
本申请实施例提供一种采集指纹图像的方法、装置和电子设备，能够降低屏幕驱动和屏幕刷新对指纹检测的影响，从而提高指纹检测的性能。
一方面，提供了一种采集指纹图像的方法，包括：
分别基于N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍且小于所述预设曝光时间，N为大于或等于3的正整数；
根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度；
将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间；
基于所述目标曝光时间，控制所述指纹传感器采集指纹图像。
在一种可能的实现方式中，所述特征参数包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。
在一种可能的实现方式中，所述特征参数包括时域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；
根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
在一种可能的实现方式中，所述特征参数包括空域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；
根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
在一种可能的实现方式中，所述特征参数包括横条纹强度，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；
所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
在一种可能的实现方式中，所述第一值为所述N个值中的最小值。
在一种可能的实现方式中，所述特征参数包括信噪比，所述第一值为所述N个值中的最大值。
在一种可能的实现方式中，所述预设步长包括所述指纹传感器中相邻两行指纹传感器像素曝光结束的时间差或所述指纹传感器中相邻两行指纹传感器像素曝光起始的时间差。
在一种可能的实现方式中，所述至少一帧图像为5帧图像。
另一方面，提供了一种采集指纹图像的装置，包括：处理器，所述处理器用于：
分别基于所述N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍且小于所述预设曝光时间，N为大于或等于3的正整数；
根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度；
将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间；
基于所述目标曝光时间，控制所述指纹传感器采集指纹图像。
在一种可能的实现方式中，所述特征参数包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。
在一种可能的实现方式中，所述特征参数包括时域噪声，所述处理器具体用于：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；
根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
在一种可能的实现方式中，所述特征参数包括空域噪声，所述处理器具 体用于：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；
根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
在一种可能的实现方式中，所述特征参数包括横条纹强度，所述处理器具体用于：
基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；
根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
在一种可能的实现方式中，所述第一值为所述N个值中的最小值。
在一种可能的实现方式中，所述特征参数包括信噪比，所述第一值为所述N个值中的最大值。
在一种可能的实现方式中，所述预设步长包括所述指纹传感器中相邻两行指纹传感器像素曝光结束的时间差或所述指纹传感器中相邻两行指纹传感器像素曝光起始的时间差。
在一种可能的实现方式中，所述至少一帧图像为5帧图像。
在一种可能的实现方式中，所述采集指纹图像的装置和所述指纹传感器封装在一起。
第三方面，提供了一种电子设备，包括显示屏，指纹传感器以及在第二方面任一种实现方式中的采集指纹图像的装置，其中，所述指纹传感器用于设置在所述显示屏的下方。
基于上述技术方案，以预设曝光时间为中心，采用预设步长获取多个候选曝光时间，并确定该多个候选曝光时间所对应的特征参数的多个值，通过在多个值中选择显示屏的刷新周期对指纹传感器的指纹图像的影响程度最小的值，并将其所对应的候选曝光时间确定为目标曝光时间，进而基于该目标曝光时间进行后续的指纹采集。采用本申请技术方案所确定的目标曝光时间采集指纹图像能够使得指纹传感器在对应于特定显示屏时所达到的性能最优，也就是说，可以使得显示屏的刷新周期对指纹传感器的指纹图像的影 响程度最小，即指纹图像中的横条纹最弱或者没有横条纹。
附图说明
图1是显示器的调光周期的示意图。
图2是采用逐行扫描的曝光方式对各行像素进行曝光的示意图。
图3是横条纹产生的原理性示意图。
图4是本申请实施例的采集指纹图像的方法的示意性框图。
图5是指纹传感器+显示屏的不同组合的特征参数的分布图。
图6是多帧图像中的横条纹所在位置的示意图。
图7是计算时域噪声的示意图。
图8是计算空域噪声的示意图。
图9是时域噪声和空域噪声在不同曝光时间下的分布图。
图10是本申请实施例的采集指纹图像的方法的示意性流程图。
图11是基于本申请实施例的采集指纹图像的方法所得到的一组候选曝光时间下所采集的指纹图像的示意图。
图12是在一组候选曝光时间下的整机的FRR的曲线图以及条纹噪声的曲线图。
图13是本申请实施例的采集指纹图像的装置的示意性框图。
图14是本申请实施例的采集指纹图像的装置的另一示意性框图。
图15是根据本申请一实施例的电子设备的定向视图。
图16是图15所示的电子设备沿A-A’的部分剖面结构示意图。
具体实施方式
下面将结合附图，对本申请实施例中的技术方案进行描述。
目前的电子设备追求较高的屏占比，需要将较多的正面器件移到屏幕下方，例如接近感应传感器和环境光传感器等。特别是环境光传感器设置于显示屏下方时，环境光传感器需要检测穿透显示屏的环境光的光强，因此，在检测环境光时极易受到显示屏亮度的影响，影响环境光检测的准确性。为此，一些显示屏为了提高环境光检测的准确性，更改了显示屏的显示方式，将用于调整显示屏亮度的调光周期内处于亮时段的长度增加(高占空比)，并降低每个调光周期内显示屏处于暗时段内的跌落幅值(高跌落比)。显示屏对 其亮度的调整，直接影响了显示屏下方的指纹传感器对指纹图像的采集，降低了指纹检测的性能。
例如图1所示的某种型号的屏幕的调光周期，该调光周期也称为跌落周期或刷新周期，一个调光周期包括亮时段和暗时段。示意性的，该调光周期T1＝4.065ms，即显示屏的刷新速率为246Hz，在图1所示的调光周期T1中，亮时段的信号强度Vmax＝1.70V，而暗时段的信号强度Vmin＝0.997V。可见，在一个调光周期的暗时段，显示屏基本没有光线输出，环境光传感器可以不受显示屏的光强影响，从而更准确地检测电子设备当前所处的环境光的光强。但这时如果用户进行指纹检测，需要利用显示屏发出的光线对指纹传感器中的像素阵列进行曝光，那么显示屏的这种显示方式，就会对指纹检测造成影响。
本申请实施例提供的采集指纹图像的方法，可以应用于采用各种曝光方式的指纹传感器，特别适用于采用逐行扫描(Rolling Shutter)的方式进行曝光的指纹传感器。图2示出了逐行扫描的曝光过程。指纹传感器阵列包括M行×N列像素，图2中以M＝7为例进行说明。如图2所示，像素阵列中的位于同一行的像素同时进行曝光，在该行像素的开始曝光一定时间后，对下一行的像素同时进行曝光。接着，按顺序对后面的各行像素依次开始进行曝光。相邻两行像素的曝光的起始时刻之间的时间差，例如通常可以等于一行像素的数据读取时间，从而使不同像素行的曝光后的数据的读取时间不重叠。然后，对M行像素的曝光后的数据进行处理，拼接形成一幅完整的图像。
指纹传感器的像素阵列中的一行像素的曝光时间，例如通常在30ms以上，而在目前应用中整个像素阵列的曝光时间已经达到了100ms，显示屏的调光周期例如通常是16.6ms、8.3ms、4.1ms等。可见，一行像素或者像素阵列的曝光时间往往大于显示屏的调光周期，曝光是像素对曝光时间内接收的光线进行叠加即积分的过程，某些像素行在对光线的积分过程中如果恰巧遇到显示屏将其亮度调暗，那么在调光周期的暗时段内，该像素行无法接收光线，会导致该像素行的数据偏小。也就是说，从曝光开始到曝光结束，像素阵列中的一些行会遇到暗时段的数量与其他行不同，如图3所示，第6行～第8行相比于其他的像素行会多遇到一个暗时段，从而导致指纹传感器对光子积分不同，以致于在指纹图像上形成横条纹。
在理想状态下，当一行像素的曝光时间是显示屏的调光周期的整数倍的 时候，由于每个像素的曝光时间内所包含的亮时段和暗时段的长度相等，所以各行像素在积分后得到的数据的水平基本一致，不会存在横条纹。然而，由于显示屏的调光系统和指纹检测系统是两套独立的系统，采用各自的时钟，在不同环境下，甚至是出厂时都不是绝对准确的，并且电子设备在使用过程中时钟也会发生不确定的偏移，从而让曝光时间偏离了显示屏的调光周期的整数倍，无法消除横条纹，时钟偏移理论值越多，这种现象会恶化，横条纹噪声幅值变强。
为此，本申请实施例提供了一种采集指纹图像的方法，能够降低屏幕驱动和屏幕刷新对指纹检测的影响，从而可以提高指纹检测的性能。
图4是本申请实施例的采集指纹图像的方法400的示意性框图。图4所示的方法400可以由处理器执行，例如，可以由电子设备的主控处理器，或者指纹识别装置(也可以称为指纹识别模组、指纹模组或指纹装置等)中的微处理器执行，也就是说，用于执行本申请实施例的采集指纹图像的方法400的装置可以与指纹传感器封装在一起，本申请实施例对方法400的执行主体不作限定。如图4所示，方法400可以包括以下步骤中的部分或全部。
在步骤S410中，分别基于N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍，N为大于或等于3的正整数。
需要说明的是，每个指纹传感器与特定的显示屏组装在一个电子设备之后，指纹传感器+显示屏的组合设定就产生了。通常，电子设备会采用固定的曝光时间控制指纹传感器采集指纹图像，例如，预先在电子设备内部存储至少一个曝光时间，当需要采用指纹传感器采集指纹图像时，电子设备可以从中调用一个曝光时间控制指纹传感器采集指纹图像。该调用的曝光时间可以理解为本申请中的预设曝光时间。
在本申请实施例中，可以采用一定的方式获取N个候选曝光时间。
可选地，可以在预设曝光时间的基础上按照一定的预设步长获得。具体地，该N个候选曝光时间可以至少包括第一曝光时间、第二曝光时间和该预设曝光时间，其中，第一曝光时间大于预设曝光时间，第二曝光时间小于预 设曝光时间，第一曝光时间与预设曝光时间的差值为预设步长的正整数倍并且小于预设曝光时间，预设曝光时间与第二曝光时间的差值也为预设步长的正整数倍并且小于预设曝光时间。该预设步长也可以理解为最小曝光时间扫描步进，也就是说，可以按照与预设曝光时间之间的差值为预设步长的正整数倍来分别确定第一曝光时间和第二曝光时间。
例如，假设预设曝光时间为A，预设步长为B，那么N个候选曝光时间从小到大依次包括A-n*B,…..,A-2*B,A-B,A,A+B,A+2*B,……,A+n*B，其中，n*B小于A。
可选地，该第一曝光时间与该预设曝光时间之差小于该预设曝光时间且该预设曝光时间与该第二曝光时间之差小于该预设曝光时间，即n*B小于A。
在一种实施例中，该第一曝光时间和该第二曝光时间可以以预设曝光时间为中心对称。换句话说，该第一曝光时间与预设曝光时间之差和预设曝光时间与第二曝光时间之差相等。
在另一种实施例中，该第一曝光时间和该第二曝光时间以预设曝光时间为中心不对称。也就是说，该第一曝光时间与预设曝光时间之差和预设曝光时间与第二曝光时间之差不相等。以上述为例，该N个候选曝光时间中的第一曝光时间为A+2*B，而该N个候选曝光时间中的第二曝光时间为A-B。
可选地，也可以在0～2倍的预设曝光时间之内的多个区间内取多个中位数。例如，预设曝光时间是100ms，0～200ms之间的中位数为100ms，0～100ms之间的中位数为50ms，100～200ms之间的中位数为150ms，而0～50ms之间的中位数为25ms，50～100ms之间的中位数为75ms，100～150ms之间的中位数为125ms，150～200ms之间的中位数为175ms。那么该N个候选曝光时间可以包括25ms，50ms，75ms，100ms，125ms，150ms以及175ms等。划分的区间越多，获得的候选曝光时间越多，则得到最优曝光时间的概率就越大，或者说最终得到的目标曝光时间与最优曝光时间越接近。
也就是说，本申请实施例对获取该N个候选曝光时间的方式不作限定。
在获取到N个候选曝光时间之后，可以分别基于该N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集固定对象的至少一帧图像。
由于本申请实施例的应用场景包括但不限于模组测试、整机测试、实验室测试以及售后等，因此，该固定对象可以是测试手指，即该至少一帧图像为指纹图像，该固定对象也可以是其他测试物，例如，该固定对象为测试砝 码，该测试砝码可以采用类肤质且表面平整的材料。
应理解，本申请实施例中的曝光时间可以是指整个像素阵列的曝光时间，也就是一帧图像的曝光时间；也可以是指一个像素行的曝光时间。
在步骤S420中，可以根据在每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度。
其中，该特征参数可以包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。其中，时域噪声用于表示图像在时间域噪声的大小，即用于表征单次按压下连续多帧图像测量的波动性。不同帧图像出现横条纹的位置不一样，其他都是一样的，当横条纹出现时，时域噪声就会变大。空域噪声则可以用来表征图像的平整度。即可以表征平整图像在三维空间域的实际平整程度。当图像中出现横条纹时，图像的平整度会遭到破坏，呈现波浪型，空域噪声就会变大。横条纹强度可以通过一定方式量化，例如可以采用峰峰值检测，进而来衡量噪声的大小。信噪比＝信号量/噪声，其中，信号量可以是指有用信号量，噪声则可以是指任何一种噪声，例如，可以是空域噪声或者时域噪声。出现横条纹时，若对信号量的影响较小，则可以忽略，噪声变大后信噪比就会下降。
采用时域噪声、空域噪声、信噪比和横条纹强度中的至少一种作为特征参数，能够准确表征横条纹的存在，映射横条纹强度，从而在获得的目标曝光时间下所采集的指纹图像受横条纹的影响会更小，进而可以提高指纹检测的性能。
在步骤S430中，将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间。
例如，若该特征参数是时域噪声，则将该N个值中的最小值所对应的曝光时间确定为目标曝光时间，即该第一值为最小值；若该特征参数是空域噪声，则将该N个值中的最小值所对应的曝光时间确定为目标曝光时间，即该第一值为最小值；若该特征参数是横条纹强度，则将该N个值中的最小值所对应的曝光时间确定为目标曝光时间；若该特征参数是信噪比，则将该N个值中的最大值所对应的曝光时间确定为目标曝光时间。
在选定目标曝光时间之后，进一步地，在步骤S440中，可以基于该目标曝光时间，控制指纹传感器采集指纹图像。具体地，指纹传感器可以在该 目标曝光时间下，采用Rolling Shutter方式进行曝光。
因此，本申请实施例的采集指纹图像的方法，以预设曝光时间为中心，采用预设步长获取多个候选曝光时间，并确定该多个候选曝光时间对应的特征参数的多个值，通过在多个值中选择显示屏的刷新周期对指纹传感器的指纹图像的影响程度最小的值，并将其所对应的候选曝光时间确定为目标曝光时间，进而基于该目标曝光时间进行后续的指纹采集。采用本申请实施例所确定的目标曝光时间采集指纹图像能够使得指纹传感器在对应特定显示屏时所达到的性能最优，也就是说，可以使得显示屏的刷新周期对指纹传感器的指纹图像的影响程度最小，即指纹图像中的横条纹最弱或者没有横条纹。
图5示出了指纹传感器+显示屏的不同组合的特征参数的分布。其中，横坐标表示曝光时间，纵坐标表示噪声强度，不同曲线表示不同的组合。同一组合中横条纹随着曲线的波动出现、消失、再出现、再消失。通常情况下时钟的偏移是固定的(偏快就一直快，偏慢就一直慢，并且偏移程度也是一致的)，所以只需要选择指纹传感器+显示屏的组合中没有条纹或者说条纹最弱的点所对应的曝光时间，即找到了该指纹传感器+显示屏的最佳曝光时间。
下面将分别以特征参数为时域噪声、空域噪声和横条纹强度为例描述本申请实施例。
在一种实施例中，所述特征参数包括时域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
指纹传感器可以采用测试砝码单次按压后连续采集5帧图像，根据该5帧图像的数据计算时域噪声。该5帧图像中所出现的横条纹的位置如图6所示，从图6中可以看出，横条纹是随机位置出现的，即多帧图像之间的横条纹并不对齐，时钟偏移越多，条纹幅值越大，时域噪声也越大。
如图7所示，P i,j1表示第1帧的第i行，第j列的像素值，P i,j2表示第2 帧的第i行，第j列的像素值，P i,j3表示第3帧的第i行，第j列的像素值，P i,j4表示第4帧的第i行，第j列的像素值，P i,j5表示第1帧的第i行，第j列的像素值。可以通过以下公式计算在一次候选曝光时间下所获得的时域噪声的值：
Tnoise i,j＝std(P i,j1～P i,j5)   (1)
Tnoise＝mean(Tnoise i,j)   (2)
其中，std表示标准差函数，mean表示平均值函数。
在另一种实施例中，所述特征参数包括空域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
同样地，指纹传感器可以采用测试砝码单次按压后连续采集5帧图像，根据该5帧图像的数据计算空域噪声。如图8所示，P i,j1表示第1帧的第i行，第j列的像素值，P i,j2表示第2帧的第i行，第j列的像素值，P i,j3表示第3帧的第i行，第j列的像素值，P i,j4表示第4帧的第i行，第j列的像素值，P i,j5表示第1帧的第i行，第j列的像素值。
可以通过以下公式计算在一次候选曝光时间下所获得的空域噪声的值：
P i,j＝mean(P i,j1～P i,j5)   (3)
Snoise＝std(P i,j)   (4)
其中，std表示标准差函数，mean表示平均值函数。
图9示出了时域噪声和空域噪声在不同曝光时间下的分布图。其中，横轴为时间，纵轴为噪声强度。不同曲线代表不同的指纹传感器+显示屏组合的噪声分布。
可选地，该P个指纹传感器像素可以是指纹传感器的所有像素，也可以是部分像素。
在另一种实施例中，所述特征参数包括横条纹强度，所述分别基于所述 N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；所述根据在所述每个曝光时间下采集的多帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
也就是说，可以采用每帧图像中的指纹传感器像素的峰峰值来量化横条纹强度。例如，可以计算每一帧图像的所有指纹传感器像素的峰峰值，即最大像素值和最小像素值的差值，然后再计算所有帧的峰峰值的平均值。
应理解，本申请实施例中的特征参数应包括但不限于上述举例所示，只要能够表征显示屏的刷新周期对指纹传感器采集指纹图像的影响程度即可。
还应理解，在每个候选曝光时间下所采集的图像帧数越多，则得到的特征参数的值越准确，但采集的图像帧数越多，指纹采集效率也越低，而为了平衡准确度和采集效率，则有选地，在每个候选曝光时间下，可以采集5帧图像。
可选地，在本申请实施例中，用于确定N个候选曝光时间的预设步长可以是指纹传感器中任意相邻的两行指纹传感器像素曝光结束的时间差或者指纹传感器中任意相邻的两行指纹传感器像素曝光起始的时间差。或者该预设步长也可以是一行指纹传感器像素的数据读取时间。
需要说明的是，在本申请实施例中，可以先确定N个候选曝光时间，然后在依次在该N个候选曝光时间下控制指纹传感器进行曝光；也可以在每确定一个候选曝光时间，即在该候选曝光时间下控制指纹传感器进行曝光，然后再确定下一个候选曝光时间。采用后者的方案，可以在较少的候选曝光时间下进行测试，就可以选择出更优的曝光时间。
可选地，在本申请实施例中，可以间隔固定周期就采用本申请实施例的技术方案来选择目标曝光时间，从而可以尽可能地使横条纹最弱化或者消除横条纹，以提高指纹识别性能。
图10示出了本申请实施例的采集指纹图像的方法的示意性流程图。如图10所示，该方法主要包括：
S1100，设定理论曝光时间A，即上文所述的预设曝光时间；
S1200，设定最小曝光时间扫描步进B，即为上文所述的预设步长；
S1300，确定A为中心，以B的倍数为步进依次确定多个候选曝光时间，例如，A-2B，A-B，A，A+B以及A+2B；
S1400，在每个候选曝光时间下分别采集5帧或更多帧测试砝码数据并保存；
S1500，计算每个候选曝光时间对应的特征参数的值，并对多个候选曝光时间对应的特征参数的值进行标记和排序，例如，A-2B，A-B，A，A+B以及A+2B对应的特征参数的值分别为C1、C2、C3、C4和C5；
S1600，从S1500中所计算出来的多个特征参数的值中选择最优的特征参数的值所对应的候选曝光时间作为指纹传感器的目标曝光时间，其中，该最优的特征参数的值是指显示屏的刷新周期对指纹传感器采集的指纹图像的影响程度最小，换句话说，该最优的特征参数的值是指横条纹最弱或者是没有横条纹时的曝光时间。以特征参数为时域噪声、空域噪声或横条纹强度为例，该最优的特征参数的值是指S1500中所计算出来的多个特征参数的值中的最小值。以特征参数为信噪比为例，该最优的特征参数的值是指S1500中所计算出来的多个特征参数的值中的最大值。例如，最优的特征参数的值为C2，那么其对应的候选曝光时间A-B则为目标曝光时间。
S1700，将目标曝光时间A-B写入电子设备的内存。
S1800，基于该目标曝光时间A-B，控制指纹传感器采集指纹图像。
图11是基于本申请实施例的技术方案所得到的一组候选曝光时间下所采集的指纹图像。图中，曝光时间中心值是100ms，也就是说，预设曝光时间为100ms。表1则示出了该组曝光时间与条纹噪声值的对应关系，其中，该条纹噪声值可以是时域噪声值，空域噪声值，条纹强度值或者是其他噪声值。
表1
候选曝光时间 98.4ms 98.8ms 99.2ms 99.6ms 100ms
条纹噪声值 7.4378 9.2556 9.1282 7.4463 4.4589
候选曝光时间 100.4ms 100.8ms 101.2ms 101.6ms  
条纹噪声值 4.4279 4.1885 7.5644 9.1670  
从表1中可以看出，100.4ms下的条纹噪声值高于100ms下的条纹噪声值，说明时钟实际偏慢，100.4ms更接近时钟的实际值。而最小值4.1885所对应 的曝光时间100.8ms可以认为是表1中所示9个候选曝光时间中的最优曝光时间，可以将该最优曝光时间确定为目标曝光时间。
图12示出了在上述一组候选曝光时间下的整机的真手指错误拒真率(False Reject Rate，FRR)的曲线图以及条纹噪声的曲线图。从图中结果来看，选取最小条纹噪声值对应的曝光时间作为目标曝光时间，FRR越低，越低代表性能越好，解锁成功率越高，也就是说，选取条纹噪声值越小的曝光时间，可以得到越优异的整机性能。
上文中详细描述了根据本申请实施例的采集指纹图像的方法，下面将结合图13，描述根据本申请实施例的采集指纹图像的装置，方法实施例所描述的技术特征适用于以下装置实施例。
图13示出了本申请实施例的采集指纹图像的装置1300的示意性框图。如图13所示，该装置1300包括:
控制单元1310，用于分别基于所述N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍且小于所述预设曝光时间，N为大于或等于3的正整数；
确定单元1320，用于根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度，以及
将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间；
所述控制单元1310还用于：
基于所述目标曝光时间，控制所述指纹传感器采集指纹图像。
可选地，在本申请实施例中，所述特征参数包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。
可选地，在本申请实施例中，所述特征参数包括时域噪声，所述处理器具体1310用于：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N 的正整数；获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
可选地，在本申请实施例中，所述特征参数包括空域噪声，所述处理器1310具体用于：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
可选地，在本申请实施例中，所述特征参数包括横条纹强度，所述处理器1310具体用于：基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
可选地，在本申请实施例中，所述第一值为所述N个值中的最小值。
可选地，在本申请实施例中，所述特征参数包括信噪比，所述第一值为所述N个值中的最大值。
可选地，在本申请实施例中，所述预设步长包括所述指纹传感器中相邻两行指纹传感器像素曝光结束的时间差或所述指纹传感器中相邻两行指纹传感器像素曝光起始的时间差。
可选地，在本申请实施例中，所述至少一帧图像为5帧图像。
可选地，在本申请实施例中，所述装置和所述指纹传感器封装在一起。
图14示出了本申请实施例的另一种采集指纹图像的装置1400的示意结构图。图14所示的采集指纹图像的装置1400包括处理器1410，处理器1410可以从存储器中调用并运行计算机程序，以实现本申请实施例中的方法。
可选地，如图14所示，采集指纹图像的装置1400还可以包括存储器1420。其中，处理器1410可以从存储器1420中调用并运行计算机程序，以实现本申请实施例中的方法。
其中，存储器1420可以是独立于处理器1410的一个单独的器件，也可以集成在处理器1410中。
可选地，该采集指纹图像的装置1400具体可为本申请实施例的采集指 纹图像的装置1300，并且该采集指纹图像的装置1400可以实现本申请实施例的各个方法中由采集指纹图像的装置1300实现的相应流程，为了简洁，在此不再赘述。
本申请实施例还提供了一种芯片，该芯片包括处理器，处理器可以从存储器中调用并运行计算机程序，以实现本申请实施例中的方法。
可选地，该芯片可应用于本申请实施例中的采集指纹图像的装置，并且该芯片可以实现本申请实施例的各个方法中由采集指纹图像的装置实现的相应流程，为了简洁，在此不再赘述。
应理解，本申请实施例提到的芯片还可以称为系统级芯片，系统芯片，芯片系统或片上系统芯片等。
可选地，本申请实施例还提供了一种计算机可读介质，其用于存储计算机程序，以实现本申请实施例中的方法。
本申请实施例还提供了一种电子设备，包括显示屏、指纹传感器以及上述任一种采集指纹图像的装置。
其中，该指纹传感器用于设置在所述显示屏的下方。
图15和图16示出了屏下指纹识别技术可以适用的电子设备10的示意图，其中图15为电子设备10的正面示意图，图16为图15所示的电子设备10沿A-A’的部分剖面结构示意图。电子设备10包括显示屏120、设置于显示屏120下方的环境光传感器、以及指纹传感器900，该电子设备10还包括上述任一种采集指纹图像的装置，其中，该采集指纹图像的装置可以与指纹传感器900封装在一起，或者该采集指纹图像的装置为独立于指纹传感器900的处理器，例如，电子设备的主控处理器。
如图16所示，指纹传感器900包括光检测部分910和光路引导结构903。光路引导结构903设置在光检测部分910的上方。光检测部分910包括由多个像素9011组成的像素阵列901、以及与像素阵列901相连的控制电路902等。其中，如图11所示，像素阵列901所在区域或者其感应区域为指纹传感器900的指纹检测区域103。光路引导结构903用于将指纹检测区域103上的手指返回的光信号引导至像素阵列901。
本申请实施例对指纹传感器900中的光路引导结构903不做任何限定。例如，光路引导结构903可以包括由多个微透镜组成的微透镜阵列。进一步地，在微透镜阵列的下方还可以具有至少一个挡光层，其中每个挡光层上设 置有与该多个微透镜分别对应的多个开孔，并且像素阵列901包括与该多个微透镜对应的多个像素9011。每个微透镜用于将手指返回的光信号会聚到各个挡光层中对应的开孔，以使该光信号依次通过各个挡光层中对应的开孔，传输至像素阵列901中相对应的像素9011。
又例如，光路引导结构903可以包括在半导体硅片制作而成的准直器层，其具有多个准直单元或者微孔阵列，该准直单元可以是小孔。
又例如，光路引导结构903可以包括光学透镜层，其具有一个或多个透镜单元，该透镜单元可以是由一个或多个非球面透镜组成的透镜组。例如图12所示，光路引导结构可以包括镜头9031。显示屏中的发光层1201发出的光线照射手指并经手指返回的光线，可以通过镜头9031会聚至光学指纹传感器的像素阵列901。
在进行指纹检测时，显示屏120向指纹检测区域103上方的手指140发出一束光线111，光线111在手指140的表面发生反射形成反射光或者经过手指140内部散射而形成散射光。由于指纹的脊(ridge)141与谷(valley)142对于光线的反射能力不同，因此，来自指纹脊的反射光151和来自指纹谷的反射光152具有不同的光强，反射光经过光路引导结构903后，被像素阵列901接收并转换为相应的电信号，即指纹检测信号。基于该指纹检测信号便可以获得指纹图像的数据，并进一步用于指纹匹配和验证，从而在电子设备10中实现光学指纹检测的功能。
进一步地，电子设备10还可以包括用于指纹检测的激励光源。
其中，显示屏120可以采用具有自发光显示单元的显示屏，比如有机发光二极管(Organic Light-Emitting Diode，OLED)显示屏或者微型发光二极管(Micro-LED)显示屏。以采用OLED显示屏为例，指纹传感器900可以利用该OLED显示屏120中位于指纹检测区域103的显示单元作为光学指纹检测的激励光源。
作为示例而非限定，本申请实施例中的电子设备可以为终端设备、手机、平板电脑、笔记本电脑、台式机电脑、游戏设备、车载电子设备或穿戴式智能设备等便携式或移动计算设备，以及电子数据库、汽车、银行自动柜员机(Automated Teller Machine，ATM)等其他电子设备。该穿戴式智能设备包括功能全、尺寸大、可不依赖智能手机实现完整或部分功能的设备，例如智能手表或智能眼镜等，以及包括只专注于某一类应用功能并且需要和其它设 备如智能手机配合使用的设备，例如各类进行体征监测的智能手环、智能首饰等设备。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)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。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应所述以权利要求的保护范围为准。

Claims (20)

  1. 一种采集指纹图像的方法，其特征在于，包括：
    分别基于N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍且小于所述预设曝光时间，N为大于或等于3的正整数；
    根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度；
    将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间；
    基于所述目标曝光时间，控制所述指纹传感器采集指纹图像。
  2. 根据权利要求1所述的方法，其特征在于，所述特征参数包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。
  3. 根据权利要求1所述的方法，其特征在于，所述特征参数包括时域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
    所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
    获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；
    根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
  4. 根据权利要求1所述的方法，其特征在于，所述特征参数包括空域噪声，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
    所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
    获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；
    根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
  5. 根据权利要求1所述的方法，其特征在于，所述特征参数包括横条纹强度，所述分别基于所述N个候选曝光时间中的每个候选曝光时间，控制所述指纹传感器采集至少一帧图像，包括：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；
    所述根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，包括：
    根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
  6. 根据权利要求3至5中任一项所述的方法，其特征在于，所述第一值为所述N个值中的最小值。
  7. 根据权利要求1所述的方法，其特征在于，所述特征参数包括信噪比，所述第一值为所述N个值中的最大值。
  8. 根据权利要求1至7中任一项所述的方法，其特征在于，所述预设步长包括所述指纹传感器中相邻两行指纹传感器像素曝光结束的时间差或所述指纹传感器中相邻两行指纹传感器像素曝光起始的时间差。
  9. 根据权利要求1至8中任一项所述的方法，其特征在于，所述至少一帧图像为5帧图像。
  10. 一种采集指纹图像的装置，其特征在于，包括处理器，所述处理器用于：
    分别基于所述N个候选曝光时间中的每个候选曝光时间，控制指纹传感器采集至少一帧图像，所述N个候选曝光时间包括大于预设曝光时间的第一曝光时间、小于所述预设曝光时间的第二曝光时间以及所述预设曝光时间，所述第一曝光时间与所述预设曝光时间之差以及所述预设曝光时间与所述第二曝光时间之差均为预设步长的正整数倍且小于所述预设曝光时间，N为大于或等于3的正整数；
    根据在所述每个曝光时间下采集的所述至少一帧图像，确定与所述N个候选曝光时间对应的特征参数的N个值，所述特征参数用于表征显示屏的刷新周期对所述指纹传感器采集的指纹图像的影响程度；
    将所述N个值中表征所述影响程度最小的第一值所对应的候选曝光时间确定为目标曝光时间；
    基于所述目标曝光时间，控制所述指纹传感器采集指纹图像。
  11. 根据权利要求10所述的装置，其特征在于，所述特征参数包括以下参数中的至少一种：时域噪声、空域噪声、信噪比和横条纹强度。
  12. 根据权利要求10所述的装置，其特征在于，所述特征参数包括时域噪声，所述处理器具体用于：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
    获取所述M帧图像中对应于同一指纹传感器像素的像素值的标准差；
    根据P个指纹传感器像素对应的所述标准差的平均值，确定所述第i个候选曝光时间对应的时域噪声的值，P为大于1的正整数。
  13. 根据权利要求10所述的装置，其特征在于，所述特征参数包括空域噪声，所述处理器具体用于：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集M帧图像，M为大于1的正整数，i为小于或等于N的正整数；
    获取所述M帧图像中对应于同一指纹传感器像素的像素值的平均值；
    根据P个指纹传感器像素对应的所述平均值的标准差，确定所述第i个候选曝光时间对应的空域噪声的值，P为大于1的正整数。
  14. 根据权利要求10所述的装置，其特征在于，所述特征参数包括横条纹强度，所述处理器具体用于：
    基于所述N个候选曝光时间中的第i个候选曝光时间，控制所述指纹传感器采集Q帧图像，Q为正整数，i为小于或等于N的正整数；
    根据所述Q帧图像中每帧图像中多个指纹传感器像素的峰-峰值，确定所述第i个候选曝光时间对应的横条纹强度的值。
  15. 根据权利要求12至14中任一项所述的装置，其特征在于，所述第一值为所述N个值中的最小值。
  16. 根据权利要求10所述的装置，其特征在于，所述特征参数包括信 噪比，所述第一值为所述N个值中的最大值。
  17. 根据权利要求10至16中任一项所述的装置，其特征在于，所述预设步长包括所述指纹传感器中相邻两行指纹传感器像素曝光结束的时间差或所述指纹传感器中相邻两行指纹传感器像素曝光起始的时间差。
  18. 根据权利要求10至17中任一项所述的装置，其特征在于，所述至少一帧图像为5帧图像。
  19. 根据权利要求10至18中任一项所述的装置，其特征在于，所述装置和所述指纹传感器封装在一起。
  20. 一种电子设备，其特征在于，包括显示屏、所述指纹传感器和如权利要求10至19中任一项所述的装置，其中，所述指纹传感器用于设置在所述显示屏的下方。
PCT/CN2021/099016 2021-06-08 2021-06-08 采集指纹图像的方法、装置和电子设备 WO2022257027A1 (zh)

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