WO2022061841A1 - 指纹识别的方法、装置和电子设备 - Google Patents

指纹识别的方法、装置和电子设备 Download PDF

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Publication number
WO2022061841A1
WO2022061841A1 PCT/CN2020/118206 CN2020118206W WO2022061841A1 WO 2022061841 A1 WO2022061841 A1 WO 2022061841A1 CN 2020118206 W CN2020118206 W CN 2020118206W WO 2022061841 A1 WO2022061841 A1 WO 2022061841A1
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type
point
angle
pixel points
pixel
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PCT/CN2020/118206
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English (en)
French (fr)
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胡广
王伟丞
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深圳市汇顶科技股份有限公司
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Priority to PCT/CN2020/118206 priority Critical patent/WO2022061841A1/zh
Publication of WO2022061841A1 publication Critical patent/WO2022061841A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition

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  • the embodiments of the present application relate to the technical field of fingerprint identification, and more particularly, to a method, apparatus and electronic device for fingerprint identification.
  • optical fingerprint identification device brings users a safe and convenient user experience, but forged fingerprints such as fingerprint molds and printed fingerprint images made of artificial materials (eg, silica gel, white glue, etc.) hidden danger.
  • a color filter layer CF
  • the intensity of the light signal received by the pixels called the first type of pixels
  • the first type of pixels The ratio of the intensity of the light signal received by other adjacent pixels (called the first type of pixels) to determine the authenticity of the fingerprint.
  • the intensity of the light signal received by the second type of pixels is lower than the intensity of the light signal received by the first type of pixels, that is, the first type of pixels.
  • the received optical signal and the optical signal received by the second type of pixels may affect the performance of fingerprint recognition.
  • the embodiments of the present application provide a method, device and electronic device for fingerprint identification, which can effectively improve the performance of fingerprint identification.
  • a fingerprint identification method is provided, which is applied to a fingerprint identification device disposed below a display screen of an electronic device, the fingerprint identification device includes a pixel array and a color filter layer, and the pixel array includes a first type of pixel points and a second type of pixel points, the color filter layer is arranged above the second type of pixel points, the method includes: determining the angle and period of the moiré pattern in an initial fingerprint image, wherein the initial fingerprint image The image includes data of the first type of pixel point and data of the second type of pixel point, the data of the first type of pixel point is generated by the first optical signal, and the data of the second type of pixel point is generated by the second type of pixel point.
  • the first optical signal is the optical signal received by the first type of pixels and returned by reflection or scattering of the object to be identified above the display screen
  • the second optical signal is the second optical signal
  • the data and the backfilled data of the second type of pixel points are used to generate a target fingerprint image, and the target fingerprint image is used for fingerprint identification.
  • the determining the angle and period of the moiré pattern in the initial fingerprint image includes: acquiring a target image according to the initial fingerprint image; determining the angle and the period of the moiré pattern according to the target image. cycle.
  • the determining the angle and period of the moiré pattern according to the target image includes: rotating the target image so that the difference between row means in the target image is the largest or the difference between column means in the target image is the largest. The difference is the largest; the rotation angle of the target image is determined as the angle of the moiré pattern, and the interval between two valleys or two ridges of the target image is the period of the moiré pattern; wherein, the valley is the row A row or column whose mean is lower than both the upper and lower rows has a lower mean than the left and right columns, and a ridge is a row whose mean is higher than both the upper and lower rows or the column whose mean is higher than the left and right columns.
  • the determining the angle and period of the moiré pattern according to the target image includes: performing a two-dimensional Fourier transform on the target image to obtain a spectrogram; according to the spectrogram , determine the angle and period of the moiré.
  • the point with the largest amplitude in the spectrogram is a target frequency point
  • the distance of the target frequency point relative to the center of the spectrogram is the period of the moiré pattern
  • the target frequency is the angle of the moiré.
  • the target image is a fingerprint image in a middle area of the initial fingerprint image.
  • the method before the determining the angle and period of the moiré pattern according to the target image, the method further includes: performing high-pass filtering on the target image to remove the first type of moiré Interference between the data of the pixel points and the data of the second type of pixel points.
  • backfilling the second type of pixel points according to the angle and period of the moiré pattern includes: using a bilinear interpolation algorithm or The nearest neighbor interpolation algorithm backfills the second type of pixels.
  • using a bilinear interpolation algorithm to backfill the second type of pixel points according to the angle and period of the moiré pattern includes: determining according to the angle and period of the moiré pattern The coordinates of the points to be interpolated, the angle between the coordinates of the points to be interpolated and the pixels to be backfilled in the second type of pixel points are the same as the angle of the moiré pattern, the coordinates of the points to be interpolated and the pixels to be backfilled The distance between the points is an integer multiple of the period of the moiré pattern; in the first type of pixel point, the target pixel point closest to the coordinates of the point to be interpolated is selected around the coordinates of the point to be interpolated, so The target pixel points include four pixel points; the pixel points to be backfilled are backfilled based on the target pixel points.
  • using a nearest neighbor interpolation algorithm to backfill the second type of pixel points according to the angle and period of the moiré pattern includes: determining, according to the angle and period of the moiré pattern, to be The coordinates of the interpolation point, the angle between the coordinates of the point to be interpolated and the pixel points to be backfilled in the second type of pixel points is the angle of the moiré, and the difference between the coordinates of the point to be interpolated and the pixel points to be backfilled The distance between them is an integer multiple of the period of the moiré pattern; in the first type of pixel points, the target pixel point closest to the coordinates of the point to be interpolated is determined around the coordinates of the point to be interpolated; based on the The target pixel points backfill the to-be-backfilled pixel points.
  • the coordinates of the points to be interpolated are four, and the coordinates of the four points to be interpolated are respectively located in the upper left corner direction, the lower left corner direction, the upper right corner direction and the lower right corner direction of the pixel point to be backfilled ;
  • determining the target pixel point closest to the coordinates of the to-be-interpolated point around the coordinates of the to-be-interpolated point includes: in the first type of pixel points, respectively in four The target pixel point closest to the coordinates of each point to be interpolated is determined around the coordinates of each point to be interpolated in the coordinates of the points to be interpolated; the backfilling of the pixels to be backfilled based on the pixel points, The method includes: backfilling the to-be-backfilled pixel points based on the average value of the four target pixel points.
  • the method before determining the angle and period of the moiré, the method further includes: using a median filtering algorithm or a mean filtering algorithm to backfill the second type of pixel points.
  • a fingerprint identification device which is arranged under a display screen of an electronic device, and includes: a pixel array, including a first type of pixel point and a second type of pixel point; a color filter layer, arranged on the first type of pixel Above the second type of pixels; a processing unit configured to determine the angle and period of moiré in the initial fingerprint image, wherein the initial fingerprint image includes the data of the first type of pixels and the data of the second type of pixels data, the data of the first type of pixel point is generated by the first optical signal, the data of the second type of pixel point is generated by the second optical signal, and the first optical signal is received by the first type of pixel point
  • the light signal returned by reflection or scattering of the object to be identified above the display screen, and the second light signal is the light signal received by the second type of pixels and returned by reflection or scattering of the object to be identified;
  • the processing unit is further configured to, according to the angle and period of the moiré pattern, backfill the second type of pixels; the processing
  • the processing unit is specifically configured to: acquire a target image according to the initial fingerprint image; and determine the angle and period of the moiré pattern according to the target image.
  • the processing unit is specifically configured to: rotate the target image so that the difference between row averages or the difference between column averages is the largest in the target image; determine the rotation angle of the target image is the angle of the moiré pattern, and the interval between two valleys or two ridges of the target image is the period of the moiré pattern; wherein, the valley is the row or column mean value of which is lower than the upper and lower rows.
  • a ridge is a column whose row mean is higher than both upper and lower rows or a column whose mean is higher than both left and right columns.
  • the processing unit is specifically configured to: perform a two-dimensional Fourier transform on the target image to obtain a spectrogram; and determine the angle and period of the moiré pattern according to the spectrogram.
  • the point with the largest amplitude in the spectrogram is a target frequency point
  • the distance of the target frequency point relative to the center of the spectrogram is the period of the moiré pattern
  • the target frequency is the angle of the moiré.
  • the target image is a fingerprint image in a middle area of the initial fingerprint image.
  • the processing unit before determining the angle and period of the moiré pattern according to the target image, is further configured to: perform high-pass filtering on the target image to remove the first Interference between the data of one type of pixel point and the data of the second type of pixel point.
  • the processing unit is specifically configured to: use a bilinear interpolation algorithm or a nearest neighbor interpolation algorithm to backfill the second type of pixel points according to the angle and period of the moiré pattern.
  • the processing unit is specifically configured to: determine the coordinates of the point to be interpolated according to the angle and period of the moiré, the coordinates of the point to be interpolated and the backfill in the second type of pixel points
  • the angle between the pixel points is the angle of the moiré pattern
  • the distance between the coordinates of the point to be interpolated and the pixel point to be backfilled is an integer multiple of the period of the moiré pattern
  • the processing unit is specifically configured to: determine the coordinates of the point to be interpolated according to the angle and period of the moiré, the coordinates of the point to be interpolated and the backfill in the second type of pixel points
  • the angle between the pixel points is the same as the angle of the moiré pattern, and the distance between the coordinates of the point to be interpolated and the pixel point to be backfilled is an integer multiple of the period of the moiré pattern;
  • a target pixel point closest to the coordinates of the point to be interpolated is determined around the coordinates of the point to be interpolated; backfill is performed on the pixel point to be backfilled based on the target pixel point.
  • the coordinates of the points to be interpolated are four, and the coordinates of the four points to be interpolated are respectively located in the upper left corner direction, the lower left corner direction, the upper right corner direction and the lower right corner direction of the pixel point to be backfilled ;
  • the processing unit is specifically configured to: in the first type of pixel points, respectively determine the coordinates closest to the coordinates of each point to be interpolated around the coordinates of each point to be interpolated among the four coordinates of the points to be interpolated.
  • the target pixel point based on the average value of the four target pixel points, backfill the to-be-backfilled pixel point.
  • the processing unit before determining the angle and period of the moiré, is further configured to: use a median filtering algorithm or a mean filtering algorithm to backfill the second type of pixels.
  • an electronic device comprising: a display screen and the fingerprint identification device in the second aspect and any possible implementation manner thereof.
  • the second type of pixels is backfilled according to the angle and period of the moiré.
  • the pixel data based on the The data difference of the second type of pixels is small, so that the second type of pixels can be fully and accurately backfilled, and then fingerprint recognition is performed based on the backfilled data of the second type of pixels, which can effectively improve the performance of fingerprint recognition.
  • FIG. 1 is a schematic diagram of the principle of the under-screen optical fingerprint recognition technology.
  • FIG. 2 is a schematic diagram of backfilling pixel points based on the mean filtering algorithm.
  • FIG. 3 is a schematic diagram of backfilling pixels based on a median filtering algorithm.
  • FIG. 4 is a schematic diagram of a fingerprint identification method according to an embodiment of the present application.
  • FIG. 5 is a schematic diagram of determining an angle of a moiré pattern according to an embodiment of the present application.
  • FIG. 6 is a schematic diagram of backfilling the second type of pixels using a bilinear interpolation algorithm according to an embodiment of the present application.
  • FIG. 7 is a schematic diagram of backfilling the second type of pixels to be backfilled by using the nearest neighbor interpolation algorithm according to an embodiment of the present application.
  • FIG. 8 is a schematic flowchart of backfilling the second type of pixel points according to an embodiment of the present application.
  • FIG. 9 is a schematic block diagram of a fingerprint identification device according to an embodiment of the present application.
  • FIG. 10 is a schematic block diagram of an electronic device according to an embodiment of the present application.
  • fingerprint recognition technology is used in more and more electronic devices.
  • the under-screen optical fingerprint recognition technology is the most widely used.
  • the light source in the display screen 120 can emit a beam of light to the finger above the fingerprint recognition area, and the light is reflected on the surface of the finger to form reflected light or scattered inside the finger. Scattered light.
  • the embodiments of the present application collectively refer to reflected light and scattered light as reflected light. Since the ridges of the fingerprint 110 are in close contact with the display screen 120 and have a similar refractive index, most of the light on the optical path 1 and the optical path 3 is absorbed.
  • the refractive index of the display screen 120 is greater than that of the air, most of the light on the optical path 2 is reflected.
  • an optical fingerprint sensor also called an optical fingerprint chip, sensor, sensor chip, chip, etc.
  • fingerprint identification signal Based on the fingerprint identification signal, fingerprint image data can be obtained, and further fingerprint matching verification is performed, thereby realizing the optical fingerprint identification function in the electronic device.
  • forged fingerprints made of artificial materials eg, silica gel, white glue, etc.
  • fingerprint molds e.g., printed fingerprint images, and the like
  • the reflection performance of human skin tissue to specific wavelengths of light is significantly different from artificial materials such as silica gel, paper, and tape.
  • the security of fingerprint identification can be improved by arranging a color filter layer in the fingerprint identification device.
  • the color filter layer can be arranged above the second type of pixels. Since the color filter layer filters the light signal reflected by the object to be recognized, the intensity of the light signal received by the second type of pixel is lower than that of the second type of pixel. The intensity of the light signal received by a type of pixel. For different materials (eg, skin tissue and artificial materials), the intensity difference is significantly different, and therefore, based on the intensity difference, it can be determined whether the object to be recognized is a real finger.
  • the performance of fingerprint recognition may be affected.
  • the difference may cause discontinuity of the real fingerprint signal, affecting the fingerprint unlock rate.
  • a pixel point may also be referred to as a pixel, a pixel unit, a photosensitive pixel, an optical sensing unit, or the like.
  • a median filtering algorithm or a mean filtering algorithm is used to backfill the second type of pixels based on the first type of pixels around the second type of pixels.
  • Moiré pattern also called Moiré pattern, Moiré pattern, etc.
  • the pattern and amplitude of the Moiré pattern may be different for different display screens.
  • the amplitude of the moiré pattern is relatively large, the data difference between different pixel points is large, and the use of the median filtering algorithm and the mean filtering algorithm may not be able to fully backfill the second type of pixels.
  • Figure 2 is a schematic diagram of backfilling the pixels to be backfilled in the second type of pixels using the mean filter algorithm.
  • the pixel in the middle of Figure 2 ie, the pixel with a pattern
  • the mean filtering algorithm uses the average value of 8 pixels around the pixel to be backfilled (ie, the pixels labeled 1-8 in the figure) to backfill the pixel to be backfilled.
  • Figure 3 is a schematic diagram of backfilling the pixels to be backfilled by using the median filter algorithm.
  • the pixel in the middle of Figure 3 ie, the pixel with a pattern
  • the median filter The algorithm uses the median of 5 pixels in the row direction (ie, the pixels marked 1-5 in the figure) to backfill the pixels to be backfilled.
  • the mean value filtering algorithm shown in Figure 2 is used to backfill the pixels to be backfilled by using the average value of 8 pixels around the pixels to be backfilled
  • the median filtering algorithm shown in Figure 3 is used. Backfilling the pixels to be backfilled to the median value of 5 pixels is only an exemplary illustration.
  • the mean filtering algorithm two circles of 24 pixels in total around the pixels to be backfilled or other numbers of pixels can also be used.
  • the average value backfills the pixels to be backfilled.
  • the median filtering algorithm the median value of 7 pixels in the row direction or other numbers of pixels can also be used to backfill the pixels to be backfilled, which is not specifically limited in this embodiment of the present application.
  • an embodiment of the present application proposes a method for fingerprint identification, which can effectively improve the performance of fingerprint identification.
  • FIG. 4 is a schematic flowchart of a method 200 for fingerprint identification according to an embodiment of the present application.
  • the method 200 shown in FIG. 4 can be applied to a fingerprint identification device under the display screen.
  • the fingerprint identification device can include a pixel array and a color filter layer, and the pixel array includes a first type of pixel point and a second type of pixel point.
  • the color filter layer The light layer is arranged above the second type of pixels.
  • the fingerprint identification device disposed below the display screen may be: the fingerprint identification device is disposed in a partial area below the display screen, or the identification device is disposed in the entire area under the display screen.
  • the fingerprint identification device in the embodiments of the present application may also be referred to as an optical fingerprint identification module, an optical fingerprint device, a fingerprint identification module, a fingerprint module, a fingerprint collection device, etc., and the above terms can be interchanged with each other.
  • the first type of pixels may be called ordinary pixels, and the setting manner of the pixel points may be the same as the setting manner of the pixel points in the existing pixel array.
  • the second type of pixels may be called characteristic pixels, which are used to determine the authenticity of the fingerprint.
  • the setting method of the second type of pixels is different from that of the existing pixels, and a color filter layer is arranged above them.
  • the pixel points of the first type may be arranged in the edge area of the pixel array, and the pixel points of the second type may be arranged in the middle area of the pixel array.
  • the color filter layer can play the role of filtering out the light signal, which only allows the light signal in a specific wavelength range to pass.
  • the color filter layer can be a green filter material, which only allows the light signal in the green light band to pass. In this way, after the optical signal passes through the color filter layer, the wavelength band of the optical signal is narrowed, and the overall light intensity is reduced, that is, the intensity of the optical signal entering the second type of pixel point is reduced.
  • Method 200 may include some or all of the following steps.
  • the angle and period of the moiré in the initial fingerprint image (which may also be referred to as the original image) are determined.
  • the initial fingerprint image includes the data of the first type of pixel points and the data of the second type of pixel points, the data of the first type of pixel points is generated by the first optical signal, the data of the second type of pixel points is generated by the second optical signal,
  • the first light signal is the light signal received by the first type of pixels and returned by the object to be recognized above the display screen, and the second light signal is the light signal received by the second type of pixels and returned by the object to be recognized above the display screen. light signal.
  • the target image may be acquired according to the initial fingerprint image, and then the angle and period of the moiré pattern may be determined according to the target image.
  • the target image may be an initial fingerprint image.
  • the target image may be a partial fingerprint image of the initial fingerprint image.
  • the partial fingerprint image may be the fingerprint image of the middle area.
  • a partial fingerprint image is cropped from the initial fingerprint image to determine the angle and period of the moiré pattern, instead of determining the angle and period of the moiré pattern based on the entire initial fingerprint image. Since the calculated moiré angle and period are the same regardless of whether it is based on the entire fingerprint image or part of the fingerprint image, calculating the moiré angle and period based on part of the fingerprint image can reduce the amount of calculation and improve the calculation efficiency, thereby improving fingerprints. speed of recognition.
  • the method 200 may further include: performing high-pass filtering on the target image.
  • the target image can eliminate the interference of the fingerprint signal, that is, the interference of the data of the first type of pixels and the data of the second type of pixels can be eliminated.
  • the target image after high pass filtering is a moiré image.
  • the target image based on which the angle and period of the moiré are determined may be the target image without high-pass filtering, or may be the target image after high-pass filtering, or, alternatively, the angle of the moiré is determined based on the target image.
  • the target image based on can be the target image without high-pass filtering, and the target image based on which the moiré period is determined can be the target image after high-pass filtering.
  • the angle and period of the moiré pattern can be determined according to the spatial data characteristics of the target image.
  • the angle and period of the moiré pattern can be determined by means of airspace rotation.
  • the target image can be rotated so that the difference between the row mean values or the column mean value is the largest in the target image, and then the rotation angle of the target image is the moiré angle.
  • the left image is the target image before rotation
  • the right image is the target image after rotating the left image by an angle of ⁇
  • the angle of the moiré pattern is ⁇ .
  • the interval between two valleys or two ridges of the rotated target image may be a period of moiré.
  • the valley is the column whose row mean is lower than the upper and lower rows or the column mean is lower than the left and right columns
  • the ridge is the row whose row mean is higher than the upper and lower rows or the column whose mean is higher than the left and right columns.
  • the row mean of the target row can be compared with the row mean of the upper and lower rows of the target row. If the row mean of the target row is lower than the row mean of the upper and lower rows, the target row can be The row is determined as the valley of the moiré. If the row mean of the target row is higher than the row mean of the upper and lower rows, the target row can be determined as the ridge of the moiré.
  • the column mean of the target column can be compared with the column mean of the left and right columns of the target column. If the column mean of the target column is lower than the column mean of the left and right columns, the target column can be determined as the valley of the moiré pattern. , if the column mean of the target column is higher than the column mean of the left and right columns, the target column can be determined as the ridge of the moiré pattern.
  • high-pass filtering may be performed on the rotated target image, and then the period of the moiré pattern may be determined based on the high-pass filtered target image.
  • the angle and period of the moiré pattern may be determined according to the frequency domain data characteristics of the target image.
  • a two-dimensional Fourier Transform can be performed on the target image to obtain a spectrogram, and then the angle and period of the moiré pattern can be determined according to the spectrogram.
  • the point with the largest amplitude in the spectrogram is the target frequency point
  • the distance of the target frequency point relative to the center of the spectrogram can be the period of the moiré pattern
  • the angle of the target frequency point relative to the center position of the spectrogram can be the angle of the moiré pattern .
  • the method 200 may further include: using a median filtering algorithm or a mean filtering algorithm to initially backfill the second type of pixels. That is to say, firstly, a relatively rough backfill is performed on the second type of pixels by using the median filtering algorithm or the mean filtering algorithm.
  • a bilinear interpolation algorithm or a nearest neighbor interpolation algorithm may be used to backfill the second type of pixel points.
  • the description will be given below by backfilling one pixel point in the second type of pixel point, and this one pixel point is referred to as the pixel point to be backfilled.
  • Using a bilinear interpolation algorithm to backfill the backfill to be backfilled may include: determining the coordinates of the point to be interpolated according to the angle and period of the moiré pattern, wherein the angle between the coordinates of the point to be interpolated and the pixel point to be backfilled is the angle of the moiré pattern.
  • the distance between the coordinates of the interpolation point and the pixel point to be backfilled is an integer multiple of the period of the moiré pattern.
  • the target pixel point selects the target pixel point closest to the coordinates of the point to be interpolated around the coordinates of the point to be interpolated, the target pixel point includes four pixel points, and then perform bilinear interpolation with the coordinate deviation as the weight , calculates a piece of data to be interpolated based on the four pixel points, and backfills the pixel points to be backfilled based on the calculated data to be interpolated.
  • the bilinear interpolation is performed with the coordinate deviation as the weight, and the implementation of calculating a data to be interpolated based on the four pixel points may refer to the basic principle of the bilinear interpolation algorithm, which is not repeated in this embodiment of the present application.
  • the coordinates of the points to be interpolated may be 1, 2, 3 or 4.
  • the coordinates of the multiple points to be interpolated may be located at at least one of the following positions of the pixels to be backfilled: the upper left corner direction, the lower left corner direction, the upper right corner direction and the lower right corner direction, that is, at the pixel to be backfilled Northwest, Southwest, Northeast, and Southeast of a point.
  • the greater the number of coordinates of the points to be interpolated the more accurate and sufficient the backfill of the pixels to be backfilled, and the better the performance of fingerprint recognition.
  • FIG. 6 is an exemplary diagram in which there are four coordinates of the points to be interpolated when the bilinear interpolation algorithm is adopted, and the interval between the coordinates of the four interpolation points and the pixels to be backfilled is one cycle.
  • the x-coordinate and y-coordinate of the coordinates of the point to be interpolated can be taken up and down respectively. Find 4 pixel points close to the coordinates of the point to be interpolated, such as the pixel points labeled 1, 2, 3 and 4 as shown in FIG. 6 .
  • the average value of the plurality of data to be interpolated can be taken, and then the pixels to be backfilled can be backfilled based on the obtained mean value. point.
  • the calculated data to be interpolated is A; for the coordinates of the point to be interpolated in the upper right corner, the calculated data to be interpolated is B; for the coordinates of the point to be interpolated in the lower left corner, The calculated data to be interpolated is C; for the coordinates of the point to be interpolated in the lower right corner, the calculated data to be interpolated is D.
  • the average value of the data A, B, C and D to be interpolated is calculated, and the pixel points to be backfilled are backfilled based on the average value.
  • the average value may be the average value of the four data A, B, C, and D to be interpolated, or the average value may be the average value of some of the data A, B, C, and D to be interpolated.
  • the data to be interpolated in the middle position may be selected, and the pixels to be backfilled may be backfilled based on the selected data to be interpolated.
  • the target pixel includes 4 pixels when the bilinear interpolation algorithm is adopted, this method is suitable for the situation that the period of the moiré pattern is too large and the data of each pixel is not much different.
  • Using the nearest neighbor interpolation algorithm to backfill the pixel points to be backfilled may include: determining the coordinates of the points to be interpolated according to the angle and period of the moiré pattern, wherein the angle between the coordinates of the point to be interpolated and the pixel points to be backfilled is the angle of the moiré pattern, The distance between the coordinates of the point to be interpolated and the pixel point to be backfilled is an integer multiple of the period of the moiré pattern. Then, in the first type of pixel points, round to find the target pixel point closest to the coordinates of the point to be interpolated, the target pixel point includes one pixel point, and then backfill the pixel point to be backfilled based on the one pixel point.
  • the coordinates of the points to be interpolated can also be 1, 2, 3 or 4.
  • the coordinates of the multiple points to be interpolated can also be located at at least one of the following positions of the pixels to be backfilled: the upper left corner, the lower left corner, the upper right corner and the lower right corner.
  • FIG. 7 is an exemplary diagram in which there are four coordinates of the points to be interpolated when the nearest neighbor interpolation algorithm is adopted, and the interval between the coordinates of the four interpolation points and the pixels to be backfilled is one cycle.
  • the implementation method of backfilling the pixels to be backfilled can refer to the implementation method of backfilling the pixels to be backfilled in the bilinear interpolation algorithm. For the sake of brevity, the details are not repeated here.
  • the target pixel only includes one pixel when the nearest neighbor interpolation algorithm is used, this method is suitable for situations where the period of the moiré pattern is small and the data difference between each pixel is large.
  • the angle between the target pixel point and the pixel point to be backfilled is the angle of the moiré pattern
  • the interval between the target pixel point and the pixel point to be backfilled is the moiré pattern. Integer multiple of the period, in this case, the difference between the data of the target pixel point and the data of the pixel point to be backfilled is small, so that the backfill of the pixel point to be backfilled can be fully and accurately realized.
  • FIG. 8 shows a specific flowchart of backfilling the second type of pixel points according to an embodiment of the present application.
  • a median filtering algorithm can also be used to backfill the second type of pixels.
  • the middle area of the initial fingerprint image is selected as the target image.
  • the angle of the moiré pattern is determined according to the initial fingerprint image of the selected middle area.
  • the target image can be obtained according to the initial fingerprint image in the middle area, and then the angle of the moiré pattern can be determined according to the target image.
  • the target image can be an initial fingerprint image, or it can also be a moiré image.
  • the angle of the moiré pattern may be determined according to the spatial data feature or the frequency domain data feature of the target image.
  • the period of the moiré pattern is determined according to the initial fingerprint image of the selected middle area.
  • the moiré period may also be determined according to the airspace data feature of the target image.
  • the moiré period may also be determined according to the frequency domain data feature of the target image.
  • a bilinear interpolation algorithm or a nearest neighbor interpolation algorithm can be used to select target pixels in the first type of pixels according to the angle and period of the moiré pattern, and then backfill the second type of pixels based on the target pixels.
  • a target fingerprint image is generated according to the data of the first type of pixel points and the backfilled data of the second type of pixel points, and the target fingerprint image is used for fingerprint identification.
  • the method 200 can also be used to detect other biometric features, such as heart rate detection, vein identification, and the like.
  • the second type of pixels is backfilled according to the angle and period of the moiré.
  • the data based on the The data difference with the second type of pixel point is small, so that the second type of pixel point can be fully and accurately backfilled, and then fingerprint recognition is performed based on the backfilled data of the second type of pixel point, which can effectively improve the performance of fingerprint recognition.
  • the fingerprint identification method of the embodiment of the present application is described in detail above, and the fingerprint identification device of the embodiment of the present application will be described below.
  • the fingerprint identification device in the embodiment of the present application can execute the fingerprint identification method in the embodiment of the present application, and has the function of executing the corresponding method.
  • FIG. 9 shows a schematic flowchart of a fingerprint identification device 300 according to an embodiment of the present application.
  • the fingerprint identification device 300 is arranged below the display screen to realize the optical fingerprint identification under the screen. As shown in FIG. 9, the fingerprint identification device 300 includes:
  • the pixel array 310 includes a first type of pixel point and a second type of pixel point.
  • the color filter layer 320 is disposed above the second type of pixels.
  • the processing unit 330 is configured to determine the angle and period of the moiré pattern in the initial fingerprint image, wherein the initial fingerprint image includes the data of the first type of pixel point and the data of the second type of pixel point, and the data of the first type of pixel point is determined by the first type of pixel point.
  • An optical signal is generated, the data of the second type of pixel is generated by the second optical signal, the first optical signal is the optical signal received by the first type of pixel and returned by reflection or scattering of the object to be identified above the display screen, and the second optical signal is received by the first type of pixel.
  • the light signal is the light signal received by the second type of pixels and returned by reflection or scattering of the object to be identified.
  • the processing unit 330 is further configured to backfill the second type of pixel points according to the angle and period of the moiré pattern.
  • the processing unit 330 is further configured to generate a target fingerprint image according to the data of the first type of pixel points and the backfilled data of the second type of pixel points, and the target fingerprint image is used for fingerprint identification.
  • the processing unit 330 may be a central processing unit (Central Processing Unit, CPU), and the processing unit 330 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays ( FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the processing unit 330 may be specifically configured to: acquire a target image according to the initial fingerprint image; and determine the angle and period of the moiré pattern according to the target image.
  • the processing unit 330 may be specifically configured to: rotate the target image so that the difference between row averages or the difference between column averages is the largest in the target image; determine the rotation angle of the target image as moiré
  • the angle between the two valleys or two ridges of the target image is the period of the moiré pattern; among them, the valley is the row or column whose mean value is lower than the upper and lower rows or the column whose mean value is lower than the left and right columns.
  • a ridge is a row or column whose row mean is higher than both the upper and lower rows or the column whose mean is higher than both the left and right columns.
  • the processing unit 330 is specifically configured to: perform a two-dimensional Fourier transform on the target image to obtain a spectrogram; and determine the angle and period of the moiré pattern according to the spectrogram.
  • the point with the largest amplitude in the spectrogram is the target frequency point
  • the distance of the target frequency point relative to the center position of the spectrogram is the period of the moiré pattern
  • the target frequency point is relative to the center of the spectrogram.
  • the angle of the position is the angle of the moiré pattern.
  • the target image is a fingerprint image in the middle area of the initial fingerprint image.
  • the processing unit 330 before the processing unit 330 determines the angle and period of the moiré pattern according to the target image, the processing unit 330 is further configured to: perform high-pass filtering on the target image to remove the first type of pixel points. Interference between the data and the data of the second type of pixels.
  • the processing unit 330 is specifically configured to: use a bilinear interpolation algorithm or a nearest neighbor interpolation algorithm to backfill the second type of pixels according to the angle and period of the moiré pattern.
  • the processing unit 330 is specifically configured to: determine the coordinates of the point to be interpolated according to the angle and period of the moiré pattern, and determine the distance between the coordinates of the point to be interpolated and the pixels to be backfilled in the second type of pixel points.
  • the angle is the same as the angle of the moiré, and the distance between the coordinates of the point to be interpolated and the pixel to be backfilled is an integer multiple of the period of the moiré; in the first type of pixel, the coordinates of the point to be interpolated around the coordinates of the point closest to the point to be interpolated are selected.
  • the target pixel point of the interpolation point coordinates, the target pixel point includes four pixel points; based on the target pixel point, the backfill pixel point is backfilled.
  • the processing unit 330 may be specifically configured to: determine the coordinates of the point to be interpolated according to the angle and period of the moiré pattern, and determine the difference between the coordinates of the point to be interpolated and the pixels to be backfilled in the second type of pixel points.
  • the angle between them is the angle of the moiré pattern
  • the distance between the coordinates of the point to be interpolated and the pixel point to be backfilled is an integer multiple of the period of the moiré pattern
  • the coordinates of the point to be interpolated are determined to be the closest to the point to be interpolated.
  • the target pixel of the interpolation point coordinates; the backfill is to be backfilled based on the target pixel.
  • the coordinates of the points to be interpolated may be four, and the coordinates of the four points to be interpolated are respectively located in the upper left corner direction, the lower left corner direction, the upper right corner direction and the lower right corner direction of the pixel point to be backfilled;
  • the processing unit 330 can be specifically configured to: in the first type of pixel points, respectively determine the target pixel point closest to the coordinates of each point to be interpolated around the coordinates of each point to be interpolated in the coordinates of the four points to be interpolated; The average value of the target pixels, and the pixels to be backfilled are backfilled.
  • the processing unit 330 may be further configured to: use a median filtering algorithm or a mean filtering algorithm to backfill the second type of pixels.
  • the processing unit 330 may be further configured to: select the fingerprint image in the middle area in the initial fingerprint image; the processing unit 330 is specifically configured to: according to the The initial fingerprint image of the middle area, to determine the angle and period of the moiré pattern.
  • the fingerprint identification device 300 may further include: an optical component, disposed between the display screen and the pixel array 310, for converting the light signal when the object to be identified presses the fingerprint identification area of the display screen Directed or converged to pixel array 310 .
  • the optical assembly may include at least one light blocking layer and a microlens array. At least one light-blocking layer is provided with a plurality of light-passing holes, and the microlens array is arranged above the at least one light-blocking layer, and is used to convert the first optical signal reflected by the object to be recognized and the first light signal reflected by the object to be recognized when the object to be recognized is pressed against the display screen.
  • the second optical signal is collected to the plurality of light-passing holes in the at least one light blocking layer, and the first optical signal and the second optical signal are transmitted to the pixel array 310 through the plurality of light-passing holes in the at least one light blocking layer.
  • the color filter layer 320 may be disposed in the optical path between the display screen and the optical component, or the color filter layer 320 may be disposed in the optical path between the microlens array and the pixel array. Specifically, the color filter layer 320 may be disposed between the at least one light blocking layer and the microlens array.
  • the embodiment of the present application further provides an electronic device.
  • the electronic device 400 may include a display screen 410 and a fingerprint identification device 420 .
  • the fingerprint identification device 420 may be the fingerprint identification device in the foregoing embodiment, and is disposed below the display screen 410 .
  • the fingerprint identification device 420 may be capable of executing the content in the method embodiment shown in FIG. 4 .
  • the display screen 410 may be a display screen with 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 identification device 420 may use a display unit (ie, an OLED light source) of the OLED display screen located in the fingerprint identification area as an excitation light source for optical fingerprint identification.
  • the display screen 410 may emit a beam of light to the object to be identified above the fingerprint identification area.
  • the display screen 410 may be a non-self-luminous display screen, such as a liquid crystal display screen or other passive light-emitting display screens.
  • the fingerprint identification device 420 may also include an excitation light source for fingerprint identification, and the excitation light source may specifically be an infrared light source.
  • the light source or the light source of non-visible light with a specific wavelength can be arranged under the backlight module of the liquid crystal display or in the edge area under the protective cover of the electronic device, and the fingerprint identification device 420 can be arranged on the edge of the liquid crystal panel or the protective cover Below the area and guided by the optical path so that the light signal can reach the fingerprint identification device; alternatively, the fingerprint identification device 420 can also be arranged under the backlight module, and the backlight module can pass the diffusion film, brightness enhancement film, reflection film and other film layers. Apertures or other optical designs allow light signals to pass through the liquid crystal panel and backlight module and reach the fingerprint identification device 420 .
  • the display screen 410 may be a non-folding display screen or a foldable display screen, that is, a flexible display screen.
  • the electronic device in the embodiments 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-mounted electronic device, or a wearable smart device, and Electronic databases, automobiles, bank ATMs (Automated Teller Machine, ATM) and other electronic devices.
  • the wearable smart device includes full functions, large size, and can realize complete or partial functions without relying on smart phones, such as smart watches or smart glasses, etc., and only focus on a certain type of application function, which needs to cooperate with other devices such as smart phones. Use, such as various types of smart bracelets, smart jewelry and other equipment for physical monitoring.
  • the electronic device 400 may further include a transparent protective cover plate, which may be a glass cover plate or a sapphire cover plate, which is located above the display screen 410 and covers the front surface of the electronic device 400 . Therefore, in the embodiments of the present application, the so-called object to be recognized being pressed on the display screen 410 actually refers to the transparent protective cover plate pressed above the display screen 410 or the surface of the protective layer covering the transparent protective cover plate.
  • a transparent protective cover plate which may be a glass cover plate or a sapphire cover plate, which is located above the display screen 410 and covers the front surface of the electronic device 400 . Therefore, in the embodiments of the present application, the so-called object to be recognized being pressed on the display screen 410 actually refers to the transparent protective cover plate pressed above the display screen 410 or the surface of the protective layer covering the transparent protective cover plate.
  • the electronic device 400 may further include a circuit board, and the circuit board is disposed below the fingerprint identification device 420 .
  • the fingerprint identification device 420 can be adhered to the circuit board through adhesive, and can be electrically connected to the circuit board through soldering pads and metal wires.
  • the fingerprint identification device 420 can realize electrical interconnection and signal transmission with other peripheral circuits or other elements of the electronic device 400 through the circuit board.
  • the fingerprint identification device 420 can receive the control signal of the processing unit of the electronic device 400 through the circuit board, and can also output the fingerprint detection signal from the fingerprint identification device 420 to the processing unit or the control unit of the terminal device 10 through the circuit board.
  • the disclosed systems and apparatuses may be implemented in other manners.
  • the apparatus 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 may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may also be electrical, mechanical or other forms of connection.
  • the units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solutions of the embodiments of the present application.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium.
  • the technical solutions of the present application are essentially or part of contributions to the prior art, or all or part of the technical solutions can be embodied in the form of software products, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to 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 disk and other media that can store program codes .

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Abstract

本申请实施例提供了一种指纹识别的方法、装置和电子设备，可以有效提高指纹识别的性能。该方法应用于设置于电子设备的显示屏下方的指纹识别装置，指纹识别装置包括像素阵列和彩色滤光层，像素阵列包括第一类像素点和第二类像素点，彩色滤光层设置在第二类像素点上方，该方法包括：确定初始指纹图像中的摩尔纹的角度和周期，其中，初始指纹图像包括由第一光信号生成的第一类像素点的数据以及由第二光信号生成的第二类像素点的数据，第一光信号为第一类像素点接收的光信号，第二光信号为第二类像素点接收的光信号；根据摩尔纹的角度和周期，对第二类像素点进行回填；根据第一类像素点的数据和回填后的第二类像素点的数据，生成目标指纹图像。

Description

指纹识别的方法、装置和电子设备 技术领域
本申请实施例涉及指纹识别技术领域，并且更具体地，涉及一种指纹识别的方法、装置和电子设备。
背景技术
光学指纹识别装置的应用给用户带来了安全和便捷的用户体验，但是通过人工材料(例如，硅胶、白胶等)制造的指纹模具、打印的指纹图像等伪造的指纹是指纹应用中一个安全隐患。为了提高指纹识别的安全性，可以在指纹识别装置中设置彩色滤光层(Colour Filter，CF)，通过彩色滤光层下方的像素点(称为第一类像素点)接收的光信号的强度与邻近的其他像素点(称为第一类像素点)接收的光信号的强度的比值来确定指纹的真假。
由于彩色滤光层对待识别物体反射的光信号进行了过滤，使得第二类像素点接收到的光信号的强度低于第一类像素点接收到的光信号的强度，即第一类像素点接收到的光信号和第二类像素点接收到的光信号之间存在较大差异，从而可能会影响指纹识别的性能。
发明内容
本申请实施例提供一种指纹识别的方法、装置和电子设备，可以有效提高指纹识别的性能。
第一方面，提供了一种指纹识别的方法，应用于设置于电子设备的显示屏下方的指纹识别装置，所述指纹识别装置包括像素阵列和彩色滤光层，所述像素阵列包括第一类像素点和第二类像素点，所述彩色滤光层设置在所述第二类像素点上方，所述方法包括：确定初始指纹图像中的摩尔纹的角度和周期，其中，所述初始指纹图像包括所述第一类像素点的数据和所述第二类像素点的数据，所述第一类像素点的数据由第一光信号生成，所述第二类像素点的数据由第二光信号生成，所述第一光信号为所述第一类像素点接收的经由所述显示屏上方的待识别物体反射或散射而返回的光信号，所述第二光信号为所述第二类像素点接收的经由所述待识别物体反射或散射而返回的光信号；根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填；根 据所述第一类像素点的数据和回填后的所述第二类像素点的数据，生成目标指纹图像，所述目标指纹图像用于指纹识别。
在一些可能的实施例中，所述确定初始指纹图像中的摩尔纹的角度和周期，包括：根据所述初始指纹图像，获取目标图像；根据所述目标图像，确定所述摩尔纹的角度和周期。
在一些可能的实施例中，所述根据所述目标图像，确定所述摩尔纹的角度和周期，包括：旋转所述目标图像，使得所述目标图像中行均值间的差异最大或列均值间的差异最大；将所述目标图像的旋转角度确定为所述摩尔纹的角度，将所述目标图像的两个谷或两个脊之间的间隔为所述摩尔纹的周期；其中，谷为行均值均低于上下两行的行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
在一些可能的实施例中，所述根据所述目标图像，确定所述摩尔纹的角度和周期，包括：对所述目标图像进行二维傅里叶变换，得到频谱图；根据所述频谱图，确定所述摩尔纹的角度和周期。
在一些可能的实施例中，所述频谱图中的幅值最大的点为目标频点，所述目标频点相对于所述频谱图中心位置的距离为所述摩尔纹的周期，所述目标频点相对于所述频谱图中心位置的角度为所述摩尔纹的角度。
在一些可能的实施例中，所述目标图像为所述初始指纹图像中间区域的指纹图像。
在一些可能的实施例中，在所述根据所述目标图像，确定所述摩尔纹的角度和周期之前，所述方法还包括：对所述目标图像进行高通滤波，以去除所述第一类像素点的数据和所述第二类像素点的数据的干扰。
在一些可能的实施例中，所述根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填，包括：根据所述摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对所述第二类像素点进行回填。
在一些可能的实施例中，所述根据所述摩尔纹的角度和周期，采用双线性插值算法对所述第二类像素点进行回填，包括：根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度与所述摩尔纹的角度相同，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；在所述第一类像素点中，在所述待插值点坐标的周围选择最靠近所述待插值点坐标的目标像素点， 所述目标像素点包括四个像素点；基于所述目标像素点对所述待回填像素点进行回填。
在一些可能的实施例中，所述根据所述摩尔纹的角度和周期，采用最近邻插值算法对所述第二类像素点进行回填，包括：根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度为所述摩尔纹的角度，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点；基于所述目标像素点对所述待回填像素点进行回填。
在一些可能的实施例中，所述待插值点坐标为四个，所述四个待插值点坐标分别位于所述待回填像素点的左上角方向、左下角方向、右上角方向和右下角方向；
所述在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点，包括：在所述第一类像素点中，分别在四个所述待插值点坐标中的每个待插值点坐标的周围确定最靠近所述每个待插值点坐标的目标像素点；所述基于所述像素点对所述待回填像素点进行回填，包括：基于四个所述目标像素点的平均值，对所述待回填像素点进行回填。
在一些可能的实施例中，在确定所述摩尔纹的角度和周期之前，所述方法还包括：采用中值滤波算法或均值滤波算法，对所述第二类像素点进行回填。
第二方面，提供了一种指纹识别的装置，设置于电子设备的显示屏下方，包括：像素阵列，包括第一类像素点和第二类像素点；彩色滤光层，设置在所述第二类像素点上方；处理单元，用于确定初始指纹图像中的摩尔纹的角度和周期，其中，所述初始指纹图像包括所述第一类像素点的数据和所述第二类像素点的数据，所述第一类像素点的数据由第一光信号生成，所述第二类像素点的数据由第二光信号生成，所述第一光信号为所述第一类像素点接收的经由所述显示屏上方的待识别物体反射或散射而返回的光信号，所述第二光信号为所述第二类像素点接收的经由所述待识别物体反射或散射而返回的光信号；所述处理单元还用于，根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填；所述处理单元还用于，根据所述第一类像素点的数据和回填后的所述第二类像素点的数据，生成目标指纹图像，所述目标指纹 图像用于指纹识别。
在一些可能的实施例中，所述处理单元具体用于：根据所述初始指纹图像，获取目标图像；根据所述目标图像，确定所述摩尔纹的角度和周期。
在一些可能的实施例中，所述处理单元具体用于：旋转所述目标图像，使得所述目标图像中行均值间的差异最大或列均值间的差异最大；将所述目标图像的旋转角度确定为所述摩尔纹的角度，将所述目标图像的两个谷或两个脊之间的间隔为所述摩尔纹的周期；其中，谷为行均值均低于上下两行的行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
在一些可能的实施例中，所述处理单元具体用于：对所述目标图像进行二维傅里叶变换，得到频谱图；根据所述频谱图，确定所述摩尔纹的角度和周期。
在一些可能的实施例中，所述频谱图中的幅值最大的点为目标频点，所述目标频点相对于所述频谱图中心位置的距离为所述摩尔纹的周期，所述目标频点相对于所述频谱图中心位置的角度为所述摩尔纹的角度。
在一些可能的实施例中，所述目标图像为所述初始指纹图像中间区域的指纹图像。
在一些可能的实施例中，在所述根据所述目标图像，确定所述摩尔纹的角度和周期之前，所述处理单元还用于：对所述目标图像进行高通滤波，以去除所述第一类像素点的数据和所述第二类像素点的数据的干扰。
在一些可能的实施例中，所述处理单元具体用于：根据所述摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对所述第二类像素点进行回填。
在一些可能的实施例中，所述处理单元具体用于：根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度为所述摩尔纹的角度，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；在所述第一类像素点中，在所述待插值点坐标的周围选择最靠近所述待插值点坐标的目标像素点，所述目标像素点包括四个像素点；基于所述目标像素点对所述待回填像素点进行回填。
在一些可能的实施例中，所述处理单元具体用于：根据所述摩尔纹的角 度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度与所述摩尔纹的角度相同，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点；基于所述目标像素点对所述待回填像素点进行回填。
在一些可能的实施例中，所述待插值点坐标为四个，所述四个待插值点坐标分别位于所述待回填像素点的左上角方向、左下角方向、右上角方向和右下角方向；
所述处理单元具体用于：在所述第一类像素点中，分别在四个所述待插值点坐标中的每个待插值点坐标的周围确定最靠近所述每个待插值点坐标的目标像素点；基于四个所述目标像素点的平均值，对所述待回填像素点进行回填。
在一些可能的实施例中，在确定所述摩尔纹的角度和周期之前，所述处理单元还用于：采用中值滤波算法或均值滤波算法，对所述第二类像素点进行回填。
第三方面，提供一种电子设备，包括：显示屏和第二方面及其任一种可能的实现方式中的指纹识别装置。
上述技术方案，由于摩尔纹对像素的回填有一定影响，根据摩尔纹的角度和周期对第二类像素点进行回填，这样，对第二类像素点进行回填时，基于的像素点的数据与第二类像素点的数据差异较小，从而可以充分、准确地回填第二类像素点，再基于回填后的第二类像素点的数据进行指纹识别，可以有效提高指纹识别的性能。
附图说明
图1是屏下光学指纹识别技术的原理示意性图。
图2是基于均值滤波算法回填像素点的示意性图。
图3是基于中值滤波算法回填像素点的示意性图。
图4是本申请实施例的指纹识别的方法的示意性图。
图5是本申请实施例的确定摩尔纹的角度的示意性图。
图6是本申请实施例的采用双线性插值算法回填第二类像素的示意性图。
图7是本申请实施例的采用最近邻插值算法回填待回填第二类像素的示 意性图。
图8是本申请实施例的回填第二类像素点示意性流程图。
图9是本申请实施例的指纹识别装置的示意性框图。
图10是本申请实施例的电子设备的示意性框图。
具体实施方式
下面将结合附图，对本申请中的技术方案进行描述。
随着科学技术的不断发展，指纹识别技术应用在越来越多的电子设备中。其中，屏下光学指纹识别技术的应用最为广泛。
下面结合图1简单介绍一下屏下光学指纹识别技术的原理。当手指按压在显示屏120上的指纹识别区域时，显示屏120内的光源可以向指纹识别区域上方的手指发出一束光，光在手指的表面发生反射形成反射光或者经过手指内部散射而形成散射光。为了便于描述，本申请实施例将反射光和散射光统称为反射光。由于指纹110的脊(ridge)与显示屏120紧密贴合且折射率相近，光路1和光路3上的光大部分被吸收。由于指纹110的谷(valley)与显示屏120中间有空气，且显示屏120的折射率大于空气的折射率，因此光路2上的光大部分会反射。反射光经过指纹识别装置130中的透镜131后，被光学指纹传感器(也称为光学指纹芯片、传感器、传感器芯片、芯片等)所接收并转换为相应的电信号，即指纹识别信号。基于指纹识别信号便可以获得指纹图像数据，并进一步进行指纹匹配验证，从而在电子设备中实现光学指纹识别功能。
目前，通过人工材料(例如，硅胶、白胶等)制造的指纹模具、打印的指纹图像等伪造的指纹是指纹应用中一个安全隐患。受人体皮肤组织的皮层厚度、血红蛋白浓度、黑色素含量等因素的影响，人体皮肤组织对特定波长光线的反射性能与硅胶、纸张和胶带等人工材料具有显著差别。
为了解决上述问题，可以通过在指纹识别装置中设置彩色滤光层来提高指纹识别的安全性。具体而言，彩色滤光层可以设置在第二类像素点上方，由于彩色滤光层对待识别物体反射的光信号进行了过滤，使得第二类像素点接收到的光信号的强度低于第一类像素点接收到的光信号的强度。对于不同的材料(例如，皮肤组织和人工材料)而言，该强度差异明显不同，因此，基于该强度差异，可以确定待识别物体是否是真实手指。
由于第一类像素点接收到的光信号和第二类像素点接收到的光信号之间存在较大差异，可能会影响指纹识别的性能。比如，该差异可能会导致真指纹信号的不连续，影响指纹解锁率。
其中，在本申请实施例中，像素点也可以称为像素、像素单元、感光像素、光学感应单元等。
为了解决上述问题，在处理指纹图像之前，可以采用各类算法来回填第二类像素点。比如，采用中值滤波算法或均值滤波算法，基于第二类像素点周围的第一类像素点回填第二类像素点。
然而，像素点的回填方法受摩尔(Moiré)纹(也称莫尔条纹、摩尔条纹等)的影响严重，且由于显示屏结构的不同，不同显示屏的摩尔纹的条纹和幅度大小可能不一样，摩尔纹的幅度比较大时，不同像素点之间的数据差异较大，采用中值滤波算法和均值滤波算法可能并不能充分回填第二类像素点。
参考图2和图3，图2和图3的一个小方块代表一个像素点，像素点的颜色代表数据大小，像素点的颜色越黑表示像素点的数据越小，像素点的颜色越白表示像素点的越大。图2为采用均值滤波算法回填第二类像素点中的待回填像素点的示意性图，图2最中间的像素点(即带图案的像素点)为待回填像素点，从图2中可以看到，均值滤波算法采用待回填像素点周围的8个像素点(即图中标号为1-8的像素点)的平均值来回填待回填像素点。图3为采用中值滤波算法回填待回填像素点的示意性图，图3最中间的像素点(即带图案的像素点)为待回填像素点，从图3中可以看到，中值滤波算法采用行向5个像素点(即图中标号1-5的像素点)的中值来回填待回填像素点。
需要说明的是，图2所示的采用均值滤波算法，利用待回填像素点周围的8个像素点的平均值来回填待回填像素点，以及图3所示的采用中值滤波算法，利用行向5个像素点的中值来回填待回填像素点，仅为示例性说明，在采用均值滤波算法时，也可以利用待回填像素点周围两圈共24个像素点或其他数量的像素点的平均值来回填待回填像素点。同理，在采用中值滤波算法时，也可以利用行向7个像素点或其他数量的像素点的中值来回填待回填像素点，本申请实施例对此不作具体限定。
从图2和图3中可以看出来当摩尔纹的幅度较大时，不同像素点之间的 数据差异较大。如图2中的标号为5的像素点和标号为6的像素点之间的数据差异较大，待回填像素点的原始值可能很大也可能很小，在这种情况下，若采用均值滤波算法回填待回填像素点，则回填后的待回填像素点可能会存在较大偏差，从而影响指纹识别的性能。
鉴于此，本申请实施例提出了一种指纹识别的方法，可以有效提高指纹识别的性能。
图4是本申请实施例的指纹识别的方法200的示意性流程图。图4所示的方法200可以应用于显示屏下方的指纹识别装置，该指纹识别装置可以包括像素阵列和彩色滤光层，该像素阵列包括第一类像素点和第二类像素点，彩色滤光层设置在第二类像素点上方。
其中，指纹识别装置设置于显示屏下方可以为：指纹识别装置设置在显示屏下方的局部区域，或者，识别装置设置在显示屏下方的全部区域。
需要说明的是，本申请实施例中的指纹识别装置也可以称为光学指纹识别模组、光学指纹装置、指纹识别模组、指纹模组、指纹采集装置等，上述术语可相互替换。
第一类像素点可以称为普通像素点，其设置方式可以与现有的像素阵列中的像素点的设置方式相同。第二类像素点可以称为特征像素点，用于确定指纹的真假，第二类像素点的设置方式与现有的像素点的设置方式不同，其上方设置有彩色滤光层。
可选地，第一类像素点可以设置在像素阵列的边缘区域，第二类像素点可以设置在像素阵列的中间区域。
彩色滤光层可以起到滤除光信号的作用，其只允许特定波长范围内的光信号通过，例如，该彩色滤光层可以为绿色滤光材料，只允许绿光波段的光信号通过，这样，光信号经过该彩色滤光层后，光信号的波段变窄，总体光强降低，也就是说，进入该第二类像素点的光信号的强度降低。
当然，也可以在第二类像素点的上方设置其他结构，或者涂覆其他材料，只要能够达到降低进入第二类像素点的光信号强度的目的即可，本申请实施例对此不作限定。
方法200可以包括以下步骤中的部分或全部。
在210中，确定初始指纹图像(也可以称为原始图像)中的摩尔纹的角度和周期。
其中，初始指纹图像包括第一类像素点的数据和第二类像素点的数据，第一类像素点的数据由第一光信号生成，第二类像素点的数据由第二光信号生成，第一光信号为第一类像素点接收的经由显示屏上方的待识别物体反射而返回的光信号，第二光信号为第二类像素点接收的经由显示屏上方的待识别物体反射而返回的光信号。
在本申请实施例中，可以根据初始指纹图像，获取目标图像，然后再根据目标图像确定摩尔纹的角度和周期。
可选地，目标图像可以为初始指纹图像。
可选地，目标图像可以为初始指纹图像的部分指纹图像。示例性地，该部分指纹图像可以为诶中间区域的指纹图像。
在初始指纹图像中裁取部分指纹图像来确定摩尔纹的角度和周期，而不用基于整个初始指纹图像确定摩尔纹的角度和周期。由于不论是基于整个指纹图像还是部分指纹图像，计算得到的摩尔纹的角度和周期都是一样的，基于部分指纹图像计算摩尔纹的角度和周期，可以减少计算量，提高计算效率，从而提高指纹识别的速度。
可选地，在本申请实施例中，在根据目标图像确定摩尔纹的角度和周期之前，方法200还可以包括：对目标图像进行高通滤波。
由于指纹信号为高频信号，摩尔纹的信号是低频信号，对目标图像进行高通滤波可以消除指纹信号的干扰，即可以消除第一类像素点的数据和第二类像素点的数据的干扰。高通滤波后的目标图像为摩尔图像。
在这种情况下，确定摩尔纹的角度和周期时所基于的目标图像可以为未进行高通滤波的目标图像，或者，可以为高通滤波后的目标图像，又或者，确定摩尔纹的角度时所基于的目标图像可以为未进行高通滤波的目标图像，确定摩尔纹的周期时基于的目标图像可以为高通滤波后的目标图像。
在一种实现方式中，可以根据目标图像的空域数据特征，确定摩尔纹的角度和周期。示例性地，可以采用空域旋转的方式确定摩尔纹的角度和周期。
具体来说，可以旋转目标图像，使得目标图像中行均值间的差异最大或列均值间的差异最大，则目标图像的旋转角度即为摩尔纹的角度。如图5所示，左图为旋转前的目标图像，右图为将左图旋转了θ角度后的目标图像，则摩尔纹的角度为θ。
在旋转目标图像后，旋转后的目标图像的两个谷或两个脊之间的间隔可 以为摩尔纹的周期。其中，谷为行均值均低于上下两行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
在确定谷和脊的过程中，可以将目标行的行均值分别与目标行的上下两行的行均值进行比较，若目标行的行均值均低于上下两行的行均值，则可以将目标行确定为摩尔纹的谷，若目标行的行均值均高于上下两行的行均值，则可以将目标行确定为摩尔纹的脊。或者，可以将目标列的列均值分别与目标列的左右两列的列均值进行比较，若目标列的列均值均低于左右两列的列均值，则可以将目标列确定为摩尔纹的谷，若目标列的列均值均高于左右两列的列均值，则可以将目标列确定为摩尔纹的脊。
在一个具体实现中，可以在确定摩尔纹的角度后，对旋转后的目标图像进行高通滤波，然后再基于高通滤波后的目标图像确定摩尔纹的周期。
在另一种实现方式中，可以根据目标图像的频域数据特征，确定摩尔纹的角度和周期。
具体而言，可以对目标图像进行二维傅里叶变换(Fourier Transform)，得到频谱图，然后根据频谱图确定摩尔纹的角度和周期。其中，频谱图中幅值最大的点为目标频点，目标频点相对于频谱图中心位置的距离可以为摩尔纹的周期，目标频点相对于频谱图中心位置的角度可以为摩尔纹的角度。
可选地，在本申请实施例中，在确定摩尔纹的角度和周期之前，方法200还可以包括：采用中值滤波算法或均值滤波算法，对第二类像素点进行初步回填。也就是说，先采用中值滤波算法或均值滤波算法对第二类像素点进行一次比较粗糙的回填。
由于像素点的数据之间的差异较大，在频谱上可能会形成一定特征，该特征可能干扰摩尔纹的角度和周期的计算，特别是根据空域数据特征确定摩尔纹的角度和周期时，干扰最大。先对第二类像素点进行一次比较粗糙的回填，缩小像素点之间数据的差异，再根据摩尔纹的角度和周期对第二类像素点进行精确回填，可以提高回填的准确度。
在220中，根据摩尔纹的角度和周期，对第二类像素点进行回填。
在本申请实施例中，可以根据摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对第二类像素点进行回填。为了描述方便，后文以对第二类像素点中的一个像素点进行回填进行描述，将该一个像素点称为待回填像素点。
采用双线性插值算法对待回填进行回填，可以包括：根据摩尔纹的角度和周期，确定待插值点坐标，其中，待插值点坐标与待回填像素点之间的角度为摩尔纹的角度，待插值点坐标与待回填像素点之间的距离为摩尔纹的周期的整数倍。然后，在第一类像素点中，在待插值点坐标的周围选择最靠近待插值点坐标的目标像素点，该目标像素点包括四个像素点，再以坐标偏差为权重进行双线性插值，基于该四个像素点计算出一个待插值数据，基于计算得出的该待插值数据对待回填像素点进行回填。
应理解，以坐标偏差为权重进行双线性插值，基于该四个像素点计算出一个待插值数据的实现方式可以参考双线性插值算法的基本原理，本申请实施例对此不再赘述。
可选地，待插值点坐标可以为1个，2个，3个或4个。当待插值点坐标为多个时，该多个待插值点坐标可以位于待回填像素点的以下至少一个位置：左上角方向、左下角方向、右上角方向和右下角方向，即位于待回填像素点的西北方向、西南方向、东北方向以及东南方向。待插值点坐标的数量越多，对待回填像素点的回填越准确、越充分，指纹识别的性能越好。
图6为采用双线性插值算法时待插值点坐标为4个的示例性图，该4个插值点坐标与待回填像素点之前的间隔为一个周期。在确定4个待插值点坐标后，对于每个待插值点坐标(比如左上角的待插值点坐标)来说，可以针对该待插值点坐标的x坐标和y坐标，分别向上和向下取整找到靠近该待插值点坐标的4个像素点，如图6中所示的标号为1、2、3和4的像素点。
当待插值点坐标为多个时，针对每个待插值点坐标，基于四个像素点计算出一个待插值数据后，可以对多个待插值数据取均值，然后基于得到的均值回填待回填像素点。再次参考图6，针对左上角的待插值点坐标，计算得到的待插值数据为A；针对右上角的待插值点坐标，计算得到的待插值数据为B；针对左下角的待插值点坐标，计算得到的待插值数据为C；针对右下角的待插值点坐标，计算得到的待插值数据为D。之后，对待插值数据A、B、C以及D求平均值，基于该平均值回填待回填像素点。
平均值可以为待插值数据A、B、C以及D四个数据的平均值，或者可以平均值可以为待插值数据A、B、C以及D中部分数据的平均值。
或者，也可以在待插值数据A、B、C以及D中，选择处于中间位置的待插值数据，基于选择的待插值数据回填待回填像素点。
应理解，本申请实施例中的具体的例子只是为了帮助本领域技术人员更好地理解本发明实施例，而非限制本申请实施例的范围。
由于在采用双线性插值算法时，目标像素点包括4个像素点，因此该方法适用于摩尔纹的周期偏大，各个像素点的数据相差不大的情况。
采用最近邻插值算法对待回填像素点进行回填，可以包括：根据摩尔纹的角度和周期，确定待插值点坐标，其中，待插值点坐标与待回填像素点之间的角度为摩尔纹的角度，待插值点坐标与待回填像素点之间的距离为摩尔纹的周期的整数倍。然后，在第一类像素点中，四舍五入找到最靠近待插值点坐标的目标像素点，该目标像素点包括一个像素点，再基于该一个像素点对待回填像素点进行回填。
与采用双线性插值算法或最近邻插值算法对第二类像素点进行回填类似，待插值点坐标也可以为1个，2个，3个或4个。当待插值点坐标为多个时，该多个待插值点坐标同样可以位于待回填像素点的以下至少一个位置：左上角方向、左下角方向、右上角方向和右下角方向。图7为采用最近邻插值算法时待插值点坐标为4个的示例性图，该4个插值点坐标与待回填像素点之前的间隔为一个周期。
待插值点坐标的数量越多，对待回填像素点的回填越准确、越充分，指纹识别的性能越好。
当待插值点坐标有多个时，回填待回填像素点的实现方式可以参考采用双线性插值算法中回填待回填像素点的实现方式，为了内容的简洁，此处不再赘述。
由于在采用最近邻插值算法时，目标像素点只包括1个像素点，因此该方法适用于摩尔纹的周期偏小，各个像素点之间的数据差异较大的情况。
上述技术方案，基于目标像素点回填待回填像素点，该目标像素点与待回填像素点之间的角度为摩尔纹的角度，该目标像素点与待回填像素点之间的间隔为摩尔纹的周期的整数倍，这样的话目标像素点的数据与待回填的像素点的数据差异很小，如此，可以充分、准确地实现对待回填像素点的回填。
图8示出了本申请实施例的回填第二类像素点的具体流程图。
在S221中，读取第一类像素点的数据和第二类像素点的数据，生成初始指纹图像。
在S222中，采用均值滤波算法回填第二类像素点。
可选地，也可以采用中值滤波算法回填第二类像素点。
在S223中，选择初始指纹图像的中间区域作为目标图像。
在S224中，根据选择的中间区域的初始指纹图像，确定摩尔纹的角度。
其中，可以根据中间区域的初始指纹图像，获取目标图像，再根据目标图像确定摩尔纹的角度。目标图像可以为初始指纹图像，或者也可以为摩尔图像。
可选地，可以根据目标图像的空域数据特征或者频域数据特征，确定摩尔纹的角度。
在S225中，根据选择的中间区域的初始指纹图像，确定摩尔纹的周期。
若在S224中，根据目标图像的空域数据特征确定摩尔纹的角度，则S225中也可以根据目标图像的空域数据特征确定摩尔纹的周期。
若在S224中，根据目标图像的频域数据特征确定摩尔纹的角度，则S225中也可以根据目标图像的频域数据特征确定摩尔纹的周期。
在S226中，根据摩尔纹的角度和周期，再次回填第二类像素点。
其中，可以采用双线性插值算法或最邻近插值算法，根据摩尔纹的角度和周期，在第一类像素点中选择目标像素点，然后基于目标像素点对第二类像素点进行回填。
在230中，根据第一类像素点的数据和回填后的第二类像素点的数据，生成目标指纹图像，目标指纹图像用于指纹识别。
应理解，方法200除了可以进行指纹识别外，还可以用于进行其他生物特征的检测，如心率检测、静脉识别等。
本申请实施例，由于摩尔纹对像素的回填有一定影响，根据摩尔纹的角度和周期对第二类像素点进行回填，这样，对第二类像素点进行回填时，基于的像素点的数据与第二类像素点的数据差异较小，从而可以充分、准确地回填第二类像素点，再基于回填后的第二类像素点的数据进行指纹识别，可以有效提高指纹识别的性能。
上文详细描述了本申请实施例的指纹识别的方法，下面将描述本申请实施例的指纹识别装置。
应理解，本申请实施例中的指纹识别装置可以执行本申请实施例中的指纹识别的方法，具有执行相应方法的功能。
图9示出了本申请实施例的指纹识别装置300的示意性流程图。该指纹 识别装置300设置于显示屏下方，以实现屏下光学指纹识别。如图9所示，该指纹识别装置300包括：
像素阵列310，包括第一类像素点和第二类像素点。
彩色滤光层320，设置在第二类像素点上方。
处理单元330，用于确定初始指纹图像中的摩尔纹的角度和周期，其中，初始指纹图像包括第一类像素点的数据和第二类像素点的数据，第一类像素点的数据由第一光信号生成，第二类像素点的数据由第二光信号生成，第一光信号为第一类像素点接收的经由显示屏上方的待识别物体反射或散射而返回的光信号，第二光信号为第二类像素点点接收的经由待识别物体反射或散射而返回的光信号。
处理单元330还用于，根据摩尔纹的角度和周期，对第二类像素点进行回填。
处理单元330还用于，根据第一类像素点的数据和回填后的第二类像素点的数据，生成目标指纹图像，目标指纹图像用于指纹识别。
其中，处理单元330可以是中央处理单元(Central Processing Unit，CPU)，处理单元330还可以是其他通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)、现成可编程门阵列(FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
可选地，在本申请实施例中，处理单元330具体可以用于：根据初始指纹图像，获取目标图像；根据目标图像，确定摩尔纹的角度和周期。
可选地，在本申请实施例中，处理单元330具体可以用于：旋转目标图像，使得目标图像中行均值间的差异最大或列均值间的差异最大；将目标图像的旋转角度确定为摩尔纹的角度，将目标图像的两个谷或两个脊之间的间隔为摩尔纹的周期；其中，谷为行均值均低于上下两行的行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
可选地，在本申请实施例中，处理单元330具体用于：对目标图像进行二维傅里叶变换，得到频谱图；根据频谱图，确定摩尔纹的角度和周期。
可选地，在本申请实施例中，频谱图中的幅值最大的点为目标频点，目标频点相对于频谱图中心位置的距离为摩尔纹的周期，目标频点相对于频谱 图中心位置的角度为摩尔纹的角度。
可选地，在本申请实施例中，目标图像为初始指纹图像中间区域的指纹图像。
可选地，在本申请实施例中，在处理单元330根据目标图像，确定摩尔纹的角度和周期之前，处理单元330还用于：对目标图像进行高通滤波，以去除第一类像素点的数据和第二类像素点的数据的干扰。
可选地，在本申请实施例中，处理单元330具体用于：根据摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对第二类像素点进行回填。
可选地，在本申请实施例中，处理单元330具体用于：根据摩尔纹的角度和周期，确定待插值点坐标，待插值点坐标和第二类像素点中的待回填像素点之间的角度与摩尔纹的角度相同，待插值点坐标与待回填像素点之间的距离为摩尔纹的周期的整数倍；在第一类像素点中，在待插值点坐标的周围选择最靠近待插值点坐标的目标像素点，目标像素点包括四个像素点；基于目标像素点对待回填像素点进行回填。
可选地，在本申请实施例中，处理单元330具体可以用于：根据摩尔纹的角度和周期，确定待插值点坐标，待插值点坐标和第二类像素点中的待回填像素点之间的角度为摩尔纹的角度，待插值点坐标与待回填像素点之间的距离为摩尔纹的周期的整数倍；在第一类像素点中，在待插值点坐标的周围确定最靠近待插值点坐标的目标像素点；基于目标像素点对待回填像素点进行回填。
可选地，在本申请实施例中，待插值点坐标可以为四个，该四个待插值点坐标分别位于待回填像素点的左上角方向、左下角方向、右上角方向和右下角方向；
处理单元330具体可以用于：在第一类像素点中，分别在四个待插值点坐标中的每个待插值点坐标的周围确定最靠近每个待插值点坐标的目标像素点；基于四个目标像素点的平均值，对待回填像素点进行回填。
可选地，在本申请实施例中，在确定摩尔纹的角度和周期之前，处理单元330还可以用于：采用中值滤波算法或均值滤波算法，对第二类像素点进行回填。
可选地，在本申请实施例中，在确定摩尔纹的角度和周期之前，处理单元330还可以用于：在初始指纹图像中，选择中间区域的指纹图像；处理单 元330具体用于：根据中间区域的初始指纹图像，确定摩尔纹的角度和周期。
可选地，在本申请实施例中，指纹识别装置300还可以包括：光学组件，设置在显示屏和像素阵列310之间，用于在待识别物体按压显示屏的指纹识别区域时将光信号引导或会聚到像素阵列310。
光学组件可以包括至少一个阻光层和微透镜阵列。至少一个阻光层设置有多个通光小孔，微透镜阵列设置于至少一个阻光层上方，用于在待识别物体按压在显示屏时，将经过待识别物体反射的第一光信号和第二光信号汇聚至至少一个阻光层的多个通光小孔，第一光信号和第二光信号通过至少一个阻光层的多个通光小孔传输至像素阵列310。
其中，彩色滤光层320可以设置于显示屏与光学组件之间的光路中，或者，彩色滤光层320可以设置于微透镜阵列到像素阵列之间的光路中，具体地，彩色滤光层320可以设置于至少一个阻光层和微透镜阵列之间。
本申请实施例还提供了一种电子设备，如图10所示，该电子设备400可以包括显示屏410以及指纹识别装置420。该指纹识别装置420可以为前述实施例中的指纹识别装置，并设置在显示屏410下方。
其中，指纹识别装置420可以能够用于执行图4所示方法实施例中的内容。
作为一种可选的实施例，显示屏410可以为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，指纹识别装置420可以利用OLED显示屏位于指纹识别区域的显示单元(即OLED光源)作为光学指纹识别的激励光源。当待识别物体按压在指纹识别区域时，显示屏410可以向指纹识别区域上方的待识别物体发出一束光。
或者，显示屏410可以为非自发光显示屏，比如液晶显示屏或者其他的被动发光显示屏。以应用在具有背光模组和液晶面板的液晶显示屏为例，为支持液晶显示屏的屏下指纹识别，指纹识别装置420还可以包括用于指纹识别的激励光源，该激励光源可以具体为红外光源或者特定波长非可见光的光源，其可以设置在液晶显示屏的背光模组下方或者设置在电子设备的保护盖板下方的边缘区域，而指纹识别装置420可以设置液晶面板或者保护盖板的边缘区域下方并通过光路引导以使得光信号可以到达指纹识别装置；或者，指纹识别装置420也可以设置在背光模组下方，且背光模组可以通过对扩散 片、增亮片、反射片等膜层进行开孔或者其他光学设计以允许光信号穿过液晶面板和背光模组并到达指纹识别装置420。
应理解，显示屏410可以为非折叠显示屏，也可以为可折叠显示屏，即柔性显示屏。
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的功能，例如：智能手表或智能眼镜等，以及只专注于某一类应用功能，需要和其它设备如智能手机配合使用，如各类进行体征监测的智能手环、智能首饰等设备。
电子设备400还可以包括透明保护盖板，该透明保护盖板可以为玻璃盖板或者蓝宝石盖板，其位于显示屏410的上方并覆盖电子设备400的正面。因此，本申请实施例中，所谓的待识别物体按压在显示屏410实际上是指按压在显示屏410上方的透明保护盖板或者覆盖透明保护盖板的保护层表面。
此外，电子设备400还可以包括电路板，电路板设置在指纹识别装置420的下方。指纹识别装置420可以通过背胶粘接在电路板上，并通过焊盘及金属线焊接与电路板实现电性连接。指纹识别装置420可以通过电路板实现与其他外围电路或者电子设备400的其他元件的电性互连和信号传输。例如，指纹识别装置420可以通过电路板接收电子设备400的处理单元的控制信号，并且还可以通过电路板将来自指纹识别装置420的指纹检测信号输出给终端设备10的处理单元或者控制单元等。
需要说明的是，在不冲突的前提下，本申请描述的各个实施例和/或各个实施例中的技术特征可以任意的相互组合，组合之后得到的技术方案也应落入本申请的保护范围。
应理解，在本申请实施例和所附权利要求书中使用的术语是仅仅出于描述特定实施例的目的，而非旨在限制本申请实施例。例如，在本申请实施例和所附权利要求书中所使用的单数形式的“一种”、“上述”和“该”也旨在包括多数形式，除非上下文清楚地表示其他含义。
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，能够以电子硬件、计算机软件或者二者的结合来实现，为了清 楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。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。
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，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。另外，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，也可以是电的，机械的或其它的形式连接。
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申请实施例方案的目的。
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，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本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，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，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 想到各种等效的修改或替换，这些修改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以权利要求的保护范围为准。

Claims (25)

  1. 一种指纹识别的方法，其特征在于，应用于设置于电子设备的显示屏下方的指纹识别装置，所述指纹识别装置包括像素阵列和彩色滤光层，所述像素阵列包括第一类像素点和第二类像素点，所述彩色滤光层设置在所述第二类像素点上方，所述方法包括：
    确定初始指纹图像中的摩尔纹的角度和周期，其中，所述初始指纹图像包括所述第一类像素点的数据和所述第二类像素点的数据，所述第一类像素点的数据由第一光信号生成，所述第二类像素点的数据由第二光信号生成，所述第一光信号为所述第一类像素点接收的经由所述显示屏上方的待识别物体反射或散射而返回的光信号，所述第二光信号为所述第二类像素点接收的经由所述待识别物体反射或散射而返回的光信号；
    根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填；
    根据所述第一类像素点的数据和回填后的所述第二类像素点的数据，生成目标指纹图像，所述目标指纹图像用于指纹识别。
  2. 根据权利要求1所述的方法，其特征在于，所述确定初始指纹图像中的摩尔纹的角度和周期，包括：
    根据所述初始指纹图像，获取目标图像；
    根据所述目标图像，确定所述摩尔纹的角度和周期。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述目标图像，确定所述摩尔纹的角度和周期，包括：
    旋转所述目标图像，使得所述目标图像中行均值间的差异最大或列均值间的差异最大；
    将所述目标图像的旋转角度确定为所述摩尔纹的角度，将所述目标图像的两个谷或两个脊之间的间隔为所述摩尔纹的周期；
    其中，谷为行均值均低于上下两行的行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
  4. 根据权利要求2所述的方法，其特征在于，所述根据所述目标图像，确定所述摩尔纹的角度和周期，包括：
    对所述目标图像进行二维傅里叶变换，得到频谱图；
    根据所述频谱图，确定所述摩尔纹的角度和周期。
  5. 根据权利要求4所述的方法，其特征在于，所述频谱图中的幅值最大的点为目标频点，所述目标频点相对于所述频谱图中心位置的距离为所述摩尔纹的周期，所述目标频点相对于所述频谱图中心位置的角度为所述摩尔纹的角度。
  6. 根据权利要求2至5中任一项所述的方法，其特征在于，所述目标图像为所述初始指纹图像中间区域的指纹图像。
  7. 根据权利要求2至6中任一项所述的方法，其特征在于，在所述根据所述目标图像，确定所述摩尔纹的角度和周期之前，所述方法还包括：
    对所述目标图像进行高通滤波，以去除所述第一类像素点的数据和所述第二类像素点的数据的干扰。
  8. 根据权利要求1至7中任一项所述的方法，其特征在于，所述根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填，包括：
    根据所述摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对所述第二类像素点进行回填。
  9. 根据权利要求8所述的方法，其特征在于，所述根据所述摩尔纹的角度和周期，采用双线性插值算法对所述第二类像素点进行回填，包括：
    根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度为所述摩尔纹的角度，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；
    在所述第一类像素点中，在所述待插值点坐标的周围选择最靠近所述待插值点坐标的目标像素点，所述目标像素点包括四个像素点；
    基于所述目标像素点对所述待回填像素点进行回填。
  10. 根据权利要求8所述的方法，其特征在于，所述根据所述摩尔纹的角度和周期，采用最近邻插值算法对所述第二类像素点进行回填，包括：
    根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度与所述摩尔纹的角度相同，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；
    在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点；
    基于所述目标像素点对所述待回填像素点进行回填。
  11. 根据权利要求9或10所述的方法，其特征在于，所述待插值点坐标为四个，所述四个待插值点坐标分别位于所述待回填像素点的左上角方向、左下角方向、右上角方向和右下角方向；
    所述在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点，包括：
    在所述第一类像素点中，分别在四个所述待插值点坐标中的每个待插值点坐标的周围确定最靠近所述每个待插值点坐标的目标像素点；
    所述基于所述像素点对所述待回填像素点进行回填，包括：
    基于四个所述目标像素点的平均值，对所述待回填像素点进行回填。
  12. 根据权利要求1至11中任一项所述的方法，其特征在于，在确定所述摩尔纹的角度和周期之前，所述方法还包括：
    采用中值滤波算法或均值滤波算法，对所述第二类像素点进行回填。
  13. 一种指纹识别装置，其特征在于，设置于电子设备的显示屏下方，包括：
    像素阵列，包括第一类像素点和第二类像素点；
    彩色滤光层，设置在所述第二类像素点上方；
    处理单元，用于确定初始指纹图像中的摩尔纹的角度和周期，其中，所述初始指纹图像包括所述第一类像素点的数据和所述第二类像素点的数据，所述第一类像素点的数据由第一光信号生成，所述第二类像素点的数据由第二光信号生成，所述第一光信号为所述第一类像素点接收的经由所述显示屏上方的待识别物体反射或散射而返回的光信号，所述第二光信号为所述第二类像素点接收的经由所述待识别物体反射或散射而返回的光信号；
    所述处理单元还用于，根据所述摩尔纹的角度和周期，对所述第二类像素点进行回填；
    所述处理单元还用于，根据所述第一类像素点的数据和回填后的所述第二类像素点的数据，生成目标指纹图像，所述目标指纹图像用于指纹识别。
  14. 根据权利要求13所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    根据所述初始指纹图像，获取目标图像；
    根据所述目标图像，确定所述摩尔纹的角度和周期。
  15. 根据权利要求14所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    旋转所述目标图像，使得所述目标图像中行均值间的差异最大或列均值间的差异最大；
    将所述目标图像的旋转角度确定为所述摩尔纹的角度，将所述目标图像的两个谷或两个脊之间的间隔为所述摩尔纹的周期；
    其中，谷为行均值均低于上下两行的行或列均值均低于左右两列的列，脊为行均值均高于上下两行的行或列均值均高于左右两列的列。
  16. 根据权利要求14所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    对所述目标图像进行二维傅里叶变换，得到频谱图；
    根据所述频谱图，确定所述摩尔纹的角度和周期。
  17. 根据权利要求16所述的指纹识别装置，其特征在于，所述频谱图中的幅值最大的点为目标频点，所述目标频点相对于所述频谱图中心位置的距离为所述摩尔纹的周期，所述目标频点相对于所述频谱图中心位置的角度为所述摩尔纹的角度。
  18. 根据权利要求14至17中任一项所述的指纹识别装置，其特征在于，所述目标图像为所述初始指纹图像中间区域的指纹图像。
  19. 根据权利要求14至18中任一项所述的指纹识别装置，其特征在于，在所述根据所述目标图像，确定所述摩尔纹的角度和周期之前，所述处理单元还用于：
    对所述目标图像进行高通滤波，以去除所述第一类像素点的数据和所述第二类像素点的数据的干扰。
  20. 根据权利要求13至19中任一项所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    根据所述摩尔纹的角度和周期，采用双线性插值算法或最近邻插值算法对所述第二类像素点进行回填。
  21. 根据权利要求20所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度与所述摩尔纹的角度相 同，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；
    在所述第一类像素点中，在所述待插值点坐标的周围选择最靠近所述待插值点坐标的目标像素点，所述目标像素点包括四个像素点；
    基于所述目标像素点对所述待回填像素点进行回填。
  22. 根据权利要求20所述的指纹识别装置，其特征在于，所述处理单元具体用于：
    根据所述摩尔纹的角度和周期，确定待插值点坐标，所述待插值点坐标和所述第二类像素点中的待回填像素点之间的角度为所述摩尔纹的角度，所述待插值点坐标与所述待回填像素点之间的距离为所述摩尔纹的周期的整数倍；
    在所述第一类像素点中，在所述待插值点坐标的周围确定最靠近所述待插值点坐标的目标像素点；
    基于所述目标像素点对所述待回填像素点进行回填。
  23. 根据权利要求21或22所述的指纹识别装置，其特征在于，所述待插值点坐标为四个，所述四个待插值点坐标分别位于所述待回填像素点的左上角方向、左下角方向、右上角方向和右下角方向；
    所述处理单元具体用于：
    在所述第一类像素点中，分别在四个所述待插值点坐标中的每个待插值点坐标的周围确定最靠近所述每个待插值点坐标的目标像素点；
    基于四个所述目标像素点的平均值，对所述待回填像素点进行回填。
  24. 根据权利要求13至23中任一项所述的指纹识别装置，其特征在于，在确定所述摩尔纹的角度和周期之前，所述处理单元还用于：
    采用中值滤波算法或均值滤波算法，对所述第二类像素点进行回填。
  25. 一种电子设备，其特征在于，包括：
    显示屏；
    以及如权利要求13至24中任一项所述的指纹识别装置，所述指纹识别装置设置在所述显示屏的下方。
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