WO2022213382A1 - 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 PDFInfo
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Definitions
- the present application relates to the technical field of optical fingerprints, and more particularly, to a method, apparatus and electronic device for fingerprint identification.
- under-screen fingerprint recognition technology performs fingerprint recognition by imaging the difference in the ability of the ridges and valleys of the fingerprint to reflect light.
- the result of fingerprint recognition will be affected by the external environment. For example, when the terminal device is in an environment with strong illumination, the signal may exceed the range of the fingerprint device, and valid fingerprint image data cannot be obtained. Therefore, how to improve the accuracy of fingerprint recognition in the case of changes in the external environment is an urgent problem to be solved.
- the embodiments of the present application provide a method, device and electronic device for fingerprint identification, which can realize dynamic adjustment of fingerprint identification and improve fingerprint imaging quality without adding additional hardware.
- a first aspect provides a fingerprint identification method, comprising: collecting a first fingerprint image according to sampling parameters; determining a collection environment of the first fingerprint image according to the first fingerprint image and a pre-stored reference image, the reference The image is a fingerprint image obtained under a reference light environment; the first fingerprint image is processed according to the processing parameters corresponding to the collection environment; and the fingerprint identification is performed according to the processed first fingerprint image.
- the reference image may be a fingerprint image, or a simulated image simulating finger pressing under a reference light environment.
- the light characteristics of the collection environment and the pre-stored reference image are extracted from the collected fingerprint image. Compare and process the light characteristics of the fingerprint image, determine the collection environment of the fingerprint image, and process the fingerprint image according to the processing parameters corresponding to the collection environment. Since the reference image is pre-stored, the fingerprint identification device can quickly determine the fingerprint collection environment by collecting only one image, which saves time for collecting the fingerprint image and judging the fingerprint collection environment, and improves the work efficiency of the fingerprint collection device.
- the collection environment includes: the reference light environment or a non-reference light environment.
- the reference light environment includes a normal light environment with an illumination intensity of 0-1000 Lux
- the non-reference light environment includes a strong light environment with an illumination intensity greater than or equal to 1000 Lux.
- the determining the acquisition environment of the first fingerprint image according to the first fingerprint image and the pre-stored reference image includes: according to the first fingerprint image and the pre-stored reference image The pixel value difference determines the acquisition environment of the first fingerprint image.
- the determining the collection environment of the first fingerprint image according to the first fingerprint image and the pre-stored reference image includes: according to the first fingerprint image and the pre-stored reference image The change trend of the boundary pixel value of the image determines the collection environment of the first fingerprint image.
- the fingerprint identification device does not need to collect a picture with or without a backlight to compare and determine the ambient light so as to determine the fingerprint collection environment according to the ambient light, but directly
- the characteristics of the fingerprint image and the reference image can be compared to judge the collection environment, which simplifies the steps of collecting the fingerprint image and judging the collection environment, and improves the working efficiency of the fingerprint identification device.
- the determining the acquisition environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image includes: when the first fingerprint image is When the number of areas in which the average of the pixel value differences is greater than the first preset average is greater than the preset number of areas, the fingerprint recognition environment in which the fingerprint image is located is determined to be the non-reference light environment.
- the determining the acquisition environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image includes: when the first fingerprint image is When the number of areas in which the average of the pixel value differences is greater than the first preset average is less than or equal to the preset number of areas, the fingerprint recognition environment in which the fingerprint image is located is determined as the reference light environment.
- the average of the pixel value differences in the area is the average of the differences between the pixel values of the first fingerprint image in an area of the first fingerprint image and the pixel values of the corresponding area of the reference image, that is, the first fingerprint image.
- the collected fingerprint image is divided into several areas for processing, and accordingly, the reference image is also divided into several areas and compared with several areas of the fingerprint image, and the fingerprint image is refined into different areas , count the average value of the pixel value difference between each pixel point in each area and the pixel point of the corresponding reference image, and then determine whether the number of areas where the area average value is greater than the first preset average number is greater than the number of preset areas, which can be more comprehensive , Reasonably judge the overall situation of the fingerprint image.
- the first preset average number is a threshold for determining the average number of pixel value differences in each of the regions, and is positively correlated with the number of the regions.
- the determining the acquisition environment of the first fingerprint image according to the first fingerprint image and the pre-stored reference image includes: according to the first fingerprint image and the pre-stored reference image The pixel value difference value and the pixel value of the first fingerprint image determine the collection environment of the first fingerprint image.
- the acquisition environment can be more accurately determined, and the judgment of the acquisition environment by the fingerprint identification device can be further improved. ability.
- determining the collection environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image Including: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is greater than a preset ratio, and the difference between the pixel values in the first fingerprint image When the number of areas with an average number greater than the first preset average number is greater than the preset number of areas, it is determined that the collection environment of the first fingerprint image is the non-reference light environment.
- determining the collection environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image Including: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is less than or equal to a preset ratio, and/or the pixels in the first fingerprint image When the number of areas where the average of the difference values is greater than the first preset average is less than or equal to the number of preset areas, the fingerprint recognition environment where the fingerprint image is located is determined as the reference light environment.
- determining the collection environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image Including: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is greater than a preset ratio, and the average of the pixel value differences is greater than a second preset When the average number is obtained, it is determined that the acquisition environment of the first fingerprint image is the non-reference light environment.
- determining the collection environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image Including: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is less than or equal to a preset ratio, and/or the average number of pixel value differences is less than When it is equal to or equal to the second preset average number, it is determined that the collection environment of the first fingerprint image is the reference light environment.
- the second preset average is a threshold for judging the average difference between the full-image pixel values of the fingerprint image and the reference image, and can be configured according to the number of pixels.
- the fingerprint image and the reference image may not be divided into regions, and the number of pixels with saturated pixel values in the fingerprint image collected by statistics accounts for the total number of pixels in the whole image.
- the ratio of the dots, and the average of the difference between the pixel values of each pixel of the fingerprint image and the full image of the reference image are compared with the preset ratio and the second preset average, so as to avoid using only a single judgment condition for judgment.
- the error that may be caused simplifies the judgment process, and further optimizes the judgment ability of the fingerprint preparation device for the collection environment.
- the method further includes: adjusting the sampling parameter according to the non-reference light environment.
- the sampling parameters are adjusted and optimized after fingerprint identification is completed, so that the adjusted sampling parameters are used for subsequent sampling, thereby further avoiding problems caused by improper sampling parameters in a non-reference light environment.
- the fingerprint pattern is not clear and so on.
- the method further includes: adjusting the first preset average number and the preset number of regions according to the recognition result corresponding to the processed first fingerprint image.
- the method further includes: adjusting the second preset average and the preset ratio according to the recognition result corresponding to the processed first fingerprint image.
- the method further includes: adjusting the first preset average number, the preset number of areas, and the preset number according to the identification result corresponding to the processed first fingerprint image. Set the ratio.
- a corresponding fingerprint identification result is obtained after fingerprint identification is performed in a reference light environment.
- a feedback mechanism is provided, which can dynamically adjust the acquisition according to the identification result.
- the judgment parameters of the environment that is, the first preset average number, the second preset average number, the preset area quantity, and the preset ratio.
- the sampling parameters include exposure time, gain parameters and exposure areas.
- the adjusting the sampling parameter according to the non-reference light environment includes: reducing the exposure time and/or reducing the gain parameter according to the non-reference light environment.
- the adjusting the first preset average number and the preset number of regions according to the recognition result corresponding to the processed first fingerprint image includes: when the first fingerprint image is When the image recognition is unsuccessful, the first preset average number and/or the preset number of regions is adjusted down.
- the adjusting the second preset average and the preset ratio according to the recognition result corresponding to the processed first fingerprint image includes: when the first fingerprint image is When the identification is unsuccessful, the second preset average number and/or the preset ratio is adjusted down.
- a fingerprint identification device including:
- an optical fingerprint sensor used for collecting the first fingerprint image according to the sampling parameter
- a processing unit configured to determine the collection environment of the first fingerprint image according to the first fingerprint image and the pre-stored reference image, the reference image is the fingerprint image obtained under the reference light environment, and the processing corresponding to the collection environment
- the first fingerprint image is processed by parameters, and fingerprint identification is performed according to the processed first fingerprint image.
- the collection environment includes: the reference light environment or a non-reference light environment.
- the processing unit is configured to: determine a collection environment of the first fingerprint image according to a pixel value difference between the first fingerprint image and the pre-stored reference image.
- the processing unit is configured to: determine the collection environment of the first fingerprint image according to the first fingerprint image and the pre-stored change trend of boundary pixel values of the reference image.
- the processing unit is configured to: when the average number of the pixel value difference values in the multiple regions of the first fingerprint image is greater than the first preset average number, the number of regions is greater than a preset number When the number of areas is determined, the fingerprint recognition environment where the fingerprint image is located is the non-reference light environment.
- the processing unit is configured to: when the average number of the pixel value differences in the multiple regions of the first fingerprint image is greater than the first preset average number, the number of regions is less than or equal to When the number of areas is preset, the fingerprint recognition environment where the fingerprint image is located is determined as the reference light environment.
- the processing unit is configured to: determine the first fingerprint image according to a pixel value difference between the first fingerprint image and the pre-stored reference image and a pixel value of the first fingerprint image The acquisition environment of fingerprint images.
- the processing unit is configured to: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is greater than a preset ratio, and When the average of the pixel value differences is greater than the second preset average, it is determined that the collection environment of the first fingerprint image is the non-reference light environment.
- the processing unit is configured to: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is less than or equal to a preset ratio , and/or when the average of the pixel value differences is less than or equal to a second preset average, determine that the collection environment of the first fingerprint image is the reference light environment.
- the processing unit is further configured to: adjust the sampling parameter according to the non-reference light environment.
- the processing unit is further configured to: adjust the first preset average number and the preset number of regions according to the recognition result corresponding to the processed first fingerprint image.
- the processing unit is further configured to: adjust the second preset average and the preset ratio according to the recognition result corresponding to the processed first fingerprint image.
- the sampling parameters include exposure time, gain parameters and exposure areas.
- the processing unit is further configured to: reduce the exposure time and/or reduce the gain parameter according to the non-reference light environment.
- the first preset average number and/or the preset number of regions is adjusted down.
- the processing unit is further configured to: when the identification of the first fingerprint image is unsuccessful, lower the second preset average and/or the preset ratio.
- an electronic device including: a display screen, and a fingerprint identification device in any possible implementation manner of the second aspect.
- FIGS. 1A and 1B are schematic diagrams of electronic devices to which embodiments of the present application may be applied.
- FIG. 2 is a schematic flowchart of a fingerprint identification method according to an embodiment of the present application.
- FIG. 3 is a schematic diagram of several regions of a fingerprint image according to an embodiment of the present application.
- FIG. 4 is a schematic flowchart of another fingerprint identification method according to an embodiment of the present application.
- FIG. 5 is a schematic flowchart of still another fingerprint identification method according to an embodiment of the present application.
- FIG. 6 is a schematic diagram of a fingerprint identification device according to an embodiment of the present application.
- FIG. 7 is a schematic diagram of an electronic device according to an embodiment of the present application.
- embodiments of the present application can be applied to optical fingerprint systems, including but not limited to optical fingerprint recognition systems and products based on optical fingerprint imaging.
- the embodiments of the present application only take the optical fingerprint system as an example for description, but should not be implemented in this application.
- the examples constitute any limitation, and the embodiments of the present application are also applicable to other systems using optical imaging technology, and the like.
- the optical fingerprint system provided by the embodiments of the present application can be applied to smart phones, tablet computers, and other mobile terminals with display screens or other electronic devices; more specifically, in the above electronic devices, the optical fingerprint system
- the module can be arranged in a partial area or the whole area under the display screen, thereby forming an under-display (under-display or under-screen) optical fingerprint system.
- the optical fingerprint module may also be partially or fully integrated into the display screen of the electronic device, thereby forming an in-display or in-screen optical fingerprint system.
- In-display optical fingerprint detection technology uses light returned from the top surface of the device's display assembly for fingerprint sensing and other sensing operations.
- the returned light carries the information of the object in contact with the top surface, such as a finger.
- the optical fingerprint detection of a specific optical sensor module located under the display screen is realized.
- the design of the optical sensor module can be such that the desired optical imaging is achieved by properly configuring the optical elements for collecting and detecting the returned light.
- FIG. 1A is a schematic plan view of an electronic device according to an embodiment of the present application.
- the electronic device may include, but is not limited to, a mobile terminal (Mobile Terminal), a mobile phone (Mobile Phone), a user equipment (User Equipment, UE), a mobile phone (handset), a portable device (portable equipment), and the like.
- the electronic device 10 includes a display screen 120 and a fingerprint identification device 130 .
- the fingerprint identification device 130 is arranged in a partial area below the display screen 120.
- the fingerprint identification device 130 includes an optical fingerprint sensor including a sensing array 133 having a plurality of optical sensing units 131 (also referred to as pixels, photosensitive pixels, pixel units, etc.).
- the area where the sensing array 133 is located or the sensing area thereof is the fingerprint identification area 103 of the fingerprint identification device 130 .
- the fingerprint identification area 103 is located in the display area of the display screen 120 .
- the fingerprint identification device 130 is arranged at other positions, such as arranged at the side of the display screen 120 or the non-light-transmitting area of the edge of the electronic device 10, and through the optical path design, the The light signal of at least part of the display area of the display screen 120 is guided to the fingerprint recognition device 130 , so that the fingerprint recognition area 103 is actually located in the display area of the display screen 120 .
- the area of the fingerprint identification area 103 may be different from the area of the sensing array 133 of the fingerprint identification device 130, for example, an optical path design for imaging through a lens, a reflective folded optical path design, or other optical path designs such as light convergence or reflection, so that the fingerprint identification device
- the area of the fingerprint identification area 103 of the fingerprint identification device 130 is larger than that of the sensing array 133 of the fingerprint identification device 130 .
- the fingerprint identification area 103 of the fingerprint identification device 130 can also be designed to be substantially the same as the area of the sensing array 133 of the fingerprint identification device 130 .
- the electronic device 10 using the above structure does not need to reserve a space on the front of the electronic device 10 to set a fingerprint button (such as the Home button), so that a full-screen solution can be adopted, that is, the display area of the display screen 120 It can extend to substantially the entire front of the electronic device 10 .
- a fingerprint button such as the Home button
- the electronic device 10 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 120 and covers the electronic device 10 front. Therefore, in the embodiments of the present application, the so-called finger pressing on the display screen 120 actually refers to pressing the cover plate above the display screen 120 or the surface of the protective layer covering the cover plate.
- a transparent protective cover plate which may be a glass cover plate or a sapphire cover plate
- the display screen 120 can 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. display.
- OLED Organic Light-Emitting Diode
- Micro-LED micro light-emitting diode
- the fingerprint identification device 130 can use the display unit (ie, the OLED light source) of the OLED display screen 120 located in the fingerprint identification area 103 as the excitation light source for optical fingerprint detection.
- the display screen 120 When the finger 140 is pressed on the fingerprint identification area 103, the display screen 120 emits a beam of light 111 to the finger 140 above the fingerprint identification area 103, and the light 111 is reflected on the surface of the finger 140 to form reflected light or passes through all the The inside of the finger 140 is scattered to form scattered light.
- the above-mentioned reflected light and scattered light are also collectively referred to as reflected light. Since the ridges 141 and valleys 142 of the fingerprint have different reflection capabilities for light, the reflected light 151 from the fingerprint ridges and the reflected light 152 from the fingerprint valleys have different light intensities.
- the induction array 133 in the fingerprint identification device 130 After the reflected light passes through the optical components , is received by the induction array 133 in the fingerprint identification device 130 and converted into a corresponding electrical signal, that is, a fingerprint detection signal. Based on the fingerprint detection signal, fingerprint image data can be obtained, and fingerprint matching verification is further performed, thereby realizing the optical fingerprint detection function in the electronic device 10 .
- the fingerprint identification device 130 may also use a built-in light source or an external light source to provide an optical signal for fingerprint detection.
- the fingerprint identification device 130 may be suitable for a non-self-luminous display screen, such as a liquid crystal display screen or other passive light-emitting display screens.
- the optical fingerprint system of the electronic device 10 may further include an excitation light source for optical fingerprint detection, so
- the excitation light source can be specifically an infrared light source or a light source of non-visible light with a specific wavelength, which can be arranged below the backlight module of the liquid crystal display or in the edge area below the protective cover of the electronic device 10, and the fingerprint identification
- the device 130 can be arranged under the edge area of the liquid crystal panel or the protective cover and guided by the optical path so that the fingerprint detection light can reach the fingerprint identification device 130; or, the fingerprint identification device 130 can also be arranged under the backlight module, and the The backlight module allows the fingerprint detection light to pass through the liquid crystal panel and the backlight module and reach the fingerprint identification device 130 by making holes or other optical designs on film layers such as the diffusion sheet, the brightness enhancement sheet, and the reflective sheet.
- the fingerprint identification device 130 uses a built-in light source or an infrared light source or a light source of non-visible light with a specific wavelength, which can be arranged below the backlight module
- the electronic device 10 may further include a circuit board, and the circuit board is disposed below the fingerprint identification device 130 .
- the fingerprint identification device 130 can be adhered to the circuit board through adhesive backing, and is electrically connected to the circuit board through bonding pads and metal wires.
- the fingerprint identification device 130 can realize electrical interconnection and signal transmission with other peripheral circuits or other elements of the electronic device 10 through the circuit board.
- the fingerprint identification device 130 can receive the control signal of the processing unit of the electronic device 10 through the circuit board, and can also output the fingerprint detection signal from the fingerprint identification device 130 to the processing unit or the control unit of the terminal device 10 through the circuit board.
- a strong light sensing unit can be additionally set in the fingerprint sensor, according to the light signal received by the strong light sensing unit to determine whether it is currently in a strong light scene, so as to adjust the working conditions of the fingerprint recognition device when collecting fingerprint information or when The imaging conditions after the fingerprint information is collected, etc., but the additional strong light sensing unit will increase the cost of the fingerprint identification device.
- the fingerprint recognition device can collect a fingerprint picture when the display screen is lit and without light, and judge whether it is in a strong light scene according to the clarity of the fingerprints of the two pictures, but this scheme needs to collect two pictures to judge the ambient light.
- the strength and weakness of the fingerprint identification device cause the response speed of the fingerprint identification device to be relatively slow.
- an embodiment of the present application proposes a method for fingerprint identification.
- a method for fingerprint identification By pre-storing a reference image in a normal ambient light scene, only one picture needs to be collected to compare it with the pre-stored reference image to judge a strong light scene.
- the fingerprint recognition result feedback mechanism can continuously and dynamically adjust the judgment parameters of the strong light scene and the sampling parameters when collecting the fingerprint image of the fingerprint to be recognized, thereby reducing the influence of ambient light on the fingerprint collection during the fingerprint detection process.
- FIG. 2 is a schematic flowchart of a fingerprint identification method according to an embodiment of the present application.
- a first fingerprint image is collected according to the sampling parameter.
- the fingerprint identification device uses the default sampling parameters to perform sampling according to the initial sampling parameters to obtain a fingerprint image
- the sampling parameters include exposure time, exposure area, gain parameters, and the like.
- a collection environment of the first fingerprint image is determined according to the first fingerprint image and a pre-stored reference image, where the reference image is a fingerprint image obtained under a reference light environment.
- a reference image is pre-stored when the fingerprint identification device leaves the factory, and a comparison process is performed between the collected first fingerprint image and the pre-stored reference image to determine the collection environment of the first fingerprint image.
- the reference image may be a fingerprint image or a simulated image of simulating finger pressing under a reference light environment, for example, a flesh-colored pressing simulated image under a reference light environment, that is, a flesh-colored simulated finger that is close to a real finger is used to obtain the reference image.
- the collection environment includes a reference light environment and a non-reference light environment.
- the reference light environment includes a normal light environment with an illumination intensity of 0-1000 Lux
- the non-reference light environment includes a strong light environment with an illumination intensity greater than or equal to 1000 Lux.
- the first fingerprint image is processed according to processing parameters corresponding to the collection environment.
- the fingerprint identification device in the reference light environment and the non-reference light environment uses different fingerprint identification processing parameters, and the fingerprint identification device processes the fingerprint image according to the processing parameters corresponding to the collection environment after judging the collection environment.
- the processing parameters may be preset in the fingerprint identification device, or may be dynamically adjusted according to the collection environment, which is not limited in this embodiment of the present application.
- the processing parameters include pixel value quantization scale, noise floor of the optical fingerprint sensor, and the like.
- the quantized scale of pixel values under non-reference light is used to extract the fingerprint texture to obtain a clearer fingerprint image.
- the pixel value quantization scale refers to the parameters used in the process of adjusting the data collected with different exposure times and different gain parameters to the same exposure time and data corresponding to the same gain parameter.
- the exposure time for default sampling is 100 ⁇ s
- the exposure time for non-reference light environment sampling is 50 ⁇ s.
- the sampling data in non-reference light environment needs to be multiplied by the pixel value quantization scale, that is, multiplied by 2, and then compared with the data sampled under the default conditions. Compare.
- the optical fingerprint sensor uses different acquisition parameters to collect data, its sensor base is different, so it is necessary to subtract the corresponding noise floor when using different acquisition parameters to obtain the actual sensing value of the optical fingerprint sensor.
- fingerprint identification is performed according to the processed first fingerprint image.
- the light characteristics of the collection environment and the light characteristics of the pre-stored reference image are extracted from the collected fingerprint image.
- a comparison process is performed to determine the collection environment of the fingerprint image, and the fingerprint image is processed according to processing parameters corresponding to the collection environment. Since the reference image is pre-stored, the fingerprint identification device only needs to collect one image to realize the rapid judgment of the fingerprint collection environment, which saves the time for collecting the fingerprint image and judging the fingerprint collection environment, and improves the working efficiency of the fingerprint collection device.
- the processing parameters of the fingerprint image can be dynamically adjusted, and the identification performance of the fingerprint identification device can be improved.
- a collection environment of the first fingerprint image is determined according to the pixel value difference between the first fingerprint image and the pre-stored reference image.
- the fingerprint identification device collects the first fingerprint image, it counts the pixel value of each pixel of the first fingerprint image. Since the reference image has been pre-stored, the fingerprint identification device only needs to extract the pixel value information of the reference image to calculate the The difference between the pixel values of the first fingerprint image can be used to determine the collection environment of the first fingerprint image based on the difference of the pixel values. For example, when the average number of pixel value differences is greater than a preset value, it is determined that the collection environment is a non-reference environment.
- the collection environment of the first fingerprint image is determined according to the change trend of the boundary pixel value of the first fingerprint image and the pre-stored reference image.
- the fingerprint identification device collects the first fingerprint image, it counts the change trend of the pixel value of the boundary pixel points of the first fingerprint image, and extracts the change trend of the pixel value of the corresponding boundary pixel point of the reference image.
- the trend judges the collection environment of the first fingerprint image. For example, if the change trend of the boundary pixel value of the first fingerprint image is greater than the change trend of the boundary pixel value of the reference image, it is determined that the collection environment is a non-reference environment.
- the fingerprint identification device does not need to collect a picture with and without backlight to compare and determine the ambient light so as to determine the fingerprint collection environment according to the ambient light, but directly compare the collected fingerprint image with the The collection environment can be judged by comparing the features of the reference image, which simplifies the steps of collecting the fingerprint image and judging the collection environment, and improves the working efficiency of the fingerprint identification device.
- the fingerprint where the fingerprint image is located when the average number of the pixel value differences in the first fingerprint image is greater than the number of regions where the first preset average number is greater than the number of preset regions, determine the fingerprint where the fingerprint image is located.
- the identified environment is the non-reference light environment.
- the average number of the pixel value differences in the plurality of regions of the first fingerprint image is greater than the first preset average number and the number of regions is less than or equal to the preset number of regions, determine the number of regions.
- the fingerprint recognition environment where the fingerprint image is located is the reference light environment.
- the first fingerprint image 300 is divided into several regions, as shown in FIG. 3 .
- the average value of the pixel value difference of each area is counted, and the average value of the difference value of each area is compared with the average value of the pixel value of each area.
- the first preset average number is compared, count the number of areas where the difference average value is greater than the first preset average number, and only when the number of areas is greater than the preset number, determine that the collection environment is a non-reference light environment; other conditions are benchmarks light environment.
- the first preset average number is a threshold for determining the average number of pixel value differences in each of the regions, and is positively correlated with the number of the regions.
- the preset number may be configured according to the number of regions and the first preset average number.
- the collected fingerprint image is refined into several regions for judgment, so that the judgment result can more comprehensively and evenly reflect the overall ambient light condition of the entire first fingerprint image.
- the collection environment of the first fingerprint image is determined according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image.
- the fingerprint identification device After collecting the first fingerprint image, the fingerprint identification device counts the number of pixels with a given pixel value greater than a certain preset value or saturated pixel value in the entire first fingerprint image, and combines the pixels of the first fingerprint image and the reference image. Value difference, if the number of these pixels is greater than the preset number of pixels, and the pixel value difference is greater than the preset difference, it is determined that the collection environment is a non-reference environment.
- the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is greater than a preset ratio, and the pixel values in the first fingerprint image are different
- the number of areas where the average number of values is greater than the first preset average number is greater than the number of preset areas, it is determined that the collection environment of the first fingerprint image is the non-reference light environment.
- the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is less than or equal to a preset ratio, and/or the number of pixels in the first fingerprint image is When the number of areas where the average number of pixel value differences is greater than the first preset average number is less than or equal to the number of preset areas, it is determined that the fingerprint recognition environment where the fingerprint image is located is the reference light environment.
- the acquisition environment can be more accurately judged, and the ability of the fingerprint identification device to judge the acquisition environment can be further improved.
- the fingerprint identification device After collecting the first fingerprint image, the fingerprint identification device counts the proportion of pixels in the first fingerprint image whose pixel values have been saturated in the whole image, and calculates each pixel of the first fingerprint image and the whole image of the reference image. Only when the ratio is greater than the preset ratio and the average is greater than the second preset average, the acquisition environment is determined to be a non-reference light environment; otherwise, it is a reference light environment.
- the second preset average is a threshold for determining the average difference between the full-image pixel values of the fingerprint image and the reference image.
- a method for partitioning the fingerprint image can be combined, for example, using the number of pixel points with saturated pixel values in multiple areas of the fingerprint image greater than the preset number and the number of areas.
- the comparison of the preset number is used to judge the collection environment; it is also possible not to divide the fingerprint image and the reference image, and the number of pixels with saturated pixel values in the collected fingerprint image is calculated by counting the proportion of the whole image pixel points, and the fingerprint image and the fingerprint image.
- the acquisition environment can be determined by comparing the average number of pixel value differences of each pixel point in the entire reference image with the preset ratio and the second preset average number.
- the collection environment can be comprehensively judged by the judgment parameters from two angles, avoiding errors that may be caused when only a single judgment condition is used for judgment, simplifying the judgment process, and further optimizing the judgment ability of the fingerprint preparation device for the collection environment.
- FIG. 4 it is a schematic flowchart of another fingerprint identification method according to an embodiment of the present application, and the fingerprint identification method further includes:
- the fingerprint identification device processes the fingerprint image according to the processing parameters corresponding to the non-reference light environment and performs fingerprint identification, the sampling parameters are adjusted.
- the exposure time of the optical fingerprint sensor in the fingerprint identification device is reduced, so that the exposure time of subsequent sampling is shortened, and the non-reference light environment, such as a strong light environment, is over-sampled.
- the non-reference light environment such as a strong light environment
- the sensitivity gain of the optical fingerprint sensor is reduced, and the sensitivity is the luminous flux sensing amount under the unit illumination of the optical fingerprint sensor, and the sensitivity gain is reduced in a non-reference light environment, Reducing the sensing amount of the optical fingerprint sensor can reduce the probability of oversaturation of subsequent sampling images, so that the collected fingerprint images are clearer and have more effective fingerprint information.
- FIG. 5 it is a schematic flowchart of another fingerprint identification method implemented in the present application, and the method further includes:
- the first preset average number and the preset number of regions are adjusted according to the recognition result corresponding to the processed first fingerprint image.
- the fingerprint identification device processes the fingerprint image according to the processing parameters corresponding to the reference light environment and performs fingerprint identification, the fingerprint identification result is obtained.
- the fingerprint identification is unsuccessful, it means that although the light environment is determined to be normal, the fingerprint texture is still unclear. It is necessary to adjust the judgment parameters of the collection environment, such as adjusting the first preset average number and/or the preset number of areas as follows, so that the collection environment can be more easily judged as a non-reference light environment, and the processing parameters corresponding to the non-reference light environment are used. Process the fingerprint image to avoid the loss of fingerprint image details caused by improper processing parameters. For another example, when the fingerprint identification is successful, the first preset average number and/or the preset number of regions are increased, or the first preset average number and/or the preset number of regions are kept unchanged.
- the second preset average and the preset ratio are adjusted according to the identification result corresponding to the processed first fingerprint image.
- the fingerprint identification device processes the fingerprint image according to the processing parameters corresponding to the reference light environment and performs fingerprint identification
- a fingerprint identification result is obtained, and when the fingerprint identification is unsuccessful, the second preset average number and/or the preset average number and/or the preset average value are adjusted down.
- the ratio is set to make it easier for the acquisition environment to be determined as a non-reference light environment, and the fingerprint image is processed using the processing parameters corresponding to the non-reference light environment.
- the second preset average and/or the preset ratio are increased, or the second preset average and/or the preset ratio are maintained unchanged.
- the fingerprint identification device has a self-feedback mechanism, which can dynamically change the judgment parameters of the collection environment according to the fingerprint identification result, so that the fingerprint identification device can continuously adjust the judgment of the collection environment adaptively, and improve the judgment of the collection environment.
- the more flexible and accurate judgment of the collection environment enables the fingerprint identification device to use more reasonable processing parameters to process the fingerprint identification image, thereby improving the working efficiency of the fingerprint identification device.
- the fingerprint identification device includes:
- an optical fingerprint sensor 601 used for collecting a first fingerprint image according to the sampling parameter
- the processing unit 602 is configured to determine the collection environment of the first fingerprint image according to the first fingerprint image and the pre-stored reference image, where the reference image is a fingerprint image obtained under a reference light environment, and according to the corresponding collection environment.
- the processing parameter processes the first fingerprint image, and performs fingerprint identification according to the processed first fingerprint image.
- the collection environment includes a reference light environment and a non-reference light environment.
- the processing parameters include a pixel value quantization scale, a noise floor of the optical fingerprint sensor.
- the processing unit 602 uses the quantized scale of pixel values under non-reference light to extract the fingerprint texture to obtain a clearer fingerprint image.
- processing unit 602 may be executed by a processor or a processing module integrated in the fingerprint identification chip, or may be executed by a processor or a processing module in a terminal device including a fingerprint identification device, and this embodiment of the present application does not Do limit.
- the processor may be a central processing unit (Central Processing Unit, CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs) or Other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
- CPU Central Processing Unit
- DSP digital signal processor
- ASIC application specific integrated circuit
- FPGAs off-the-shelf programmable gate arrays
- a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
- the fingerprint identification device only needs to collect one fingerprint image, and the processing unit 602 can determine the collection environment of the fingerprint image by extracting the pre-stored reference image and comparing the collected fingerprint image, which saves the collection of fingerprint images and the need for judgment.
- the time of the fingerprint collection environment improves the work efficiency of the fingerprint collection device.
- the processing unit 602 is configured to: determine the collection environment of the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image.
- the processing unit 602 can extract the reference image pre-stored in the fingerprint identification device, and after the optical fingerprint sensor 601 collects the first fingerprint image, extract the pixel value feature of the first fingerprint image, and make a difference with the corresponding pixel value of the reference image to obtain Pixel value difference, according to the pixel value difference to judge the acquisition environment.
- the processing unit 602 is configured to: determine the collection environment of the first fingerprint image according to the change trend of the boundary pixel values of the first fingerprint image and the pre-stored reference image.
- the processing unit 602 is configured to: when the average number of the pixel value differences in the first fingerprint image is greater than the first preset average number of areas greater than the preset number of areas , and determine that the fingerprint recognition environment where the fingerprint image is located is the non-reference light environment.
- the processing unit 602 is configured to: determine the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image.
- a fingerprint image collection environment configured to: determine the first fingerprint image according to the pixel value difference between the first fingerprint image and the pre-stored reference image and the pixel value of the first fingerprint image.
- the processing unit 602 is configured to: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is greater than a preset ratio, And when the average of the pixel value differences is greater than the second preset average, it is determined that the collection environment of the first fingerprint image is the non-reference light environment.
- the processing unit 602 is configured to: when the ratio of the number of pixels with saturated pixel values in the first fingerprint image to the number of pixels in the first fingerprint image is less than or equal to a preset value When the ratio, and/or the average of the pixel value differences is less than or equal to the second preset average, it is determined that the collection environment of the first fingerprint image is the reference light environment.
- the processing unit 602 is further configured to: adjust the sampling parameter according to the non-reference light environment.
- the processing unit 602 adjusts the sampling parameters after identifying the fingerprint image in the non-reference light environment, controls the optical fingerprint sensor 601 to use the adjusted parameter sampling in subsequent sampling, optimizes the sampling process, and avoids the unclear texture of the fingerprint image due to the appropriate sampling parameters. And other issues.
- the processing unit 602 is further configured to: adjust the judgment parameter of the collection environment according to the identification result.
- the processing unit 602 adjusts the judgment parameters of the collection environment after identifying the fingerprint image in the non-reference light environment, and obtains the recognition result after judging the reference light environment and performing fingerprint recognition. If the recognition is unsuccessful, adjust the judgment parameters to make the collection environment more easily judged as a The non-reference light environment avoids judgment errors caused by improper judgment parameters, so that the fingerprint identification device can continuously adjust the judgment parameters through the identification results, and improve the accuracy of judging the collection environment, thereby ensuring that the fingerprint identification device adopts more reasonable corresponding processing. Parameter processing fingerprint recognition images to improve the work efficiency of the fingerprint recognition device.
- the first preset average number and the preset number of regions are adjusted according to the recognition result corresponding to the processed first fingerprint image.
- the first preset average number and/or the number of preset areas is decreased; if the identification is successful, the first preset average number and/or the number of preset areas is increased.
- the preset average number and/or the preset number of regions, or the first preset average number and/or the preset number of regions remain unchanged.
- the second preset average and the preset ratio are adjusted according to the recognition result corresponding to the processed first fingerprint image.
- the second preset average and/or the preset ratio is adjusted downward; if the identification is successful, the second preset average is adjusted upward. Setting the average and/or the preset ratio, or maintaining the second preset average and/or the preset ratio unchanged.
- an embodiment of the present application further provides an electronic device 700, including:
- the display screen 701 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 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
一种指纹识别方法,包括:根据采样参数,采集第一指纹图像;根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像;根据所述采集环境对应的处理参数处理所述第一指纹图像;根据处理后的所述第一指纹图像进行指纹识别。本申请通过预存基准图像,只需采集一张指纹图像即可判断指纹的采集环境,节省了采集指纹图像和判断采集环境的时间,有效提升了指纹识别效率。
Description
本申请涉及光学指纹技术领域,并且更具体地,涉及一种指纹识别的方法、装置和电子设备。
随着智能设备的不断发展,屏下指纹识别技术得到了广泛的应用。屏下指纹识别技术是通过指纹的脊与谷对光的反射能力的不同进行成像,从而进行指纹识别的。通常,指纹识别的结果会受到外界环境的影响,例如,当终端设备处于光照比较强的环境中,可能使信号超过指纹设备的量程,而无法得到有效的指纹图像数据。因此,如何在外界环境变化的情况下提高指纹识别的准确率,是一项亟待解决的问题。
发明内容
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,在不额外增加硬件的同时,实现指纹识别的动态调整,提高指纹成像质量。
第一方面,提供一种指纹识别的方法,包括:根据采样参数,采集第一指纹图像;根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像;根据所述采集环境对应的处理参数处理所述第一指纹图像;根据处理后的所述第一指纹图像进行指纹识别。
应理解,所述基准图像可以是指纹图像,也可以是基准光环境下模拟手指按压的模拟图像。
本申请实施例的技术方案中,通过预存基准光环境下的基准图像,在不增加额外的强光感应单元的情况下,从采集到的指纹图像中提取采集环境的光线特征与预存的基准图像的光线特征进行对比处理,判断所述指纹图像的采集环境,根据采集环境对应的处理参数处理所述指纹图像。由于预存了基准图像,指纹识别装置仅采集一张图像就能实现指纹的采集环境的快速判断,节省了采集指纹图像和判断指纹的采集环境的时间,提升了指纹采集装置的工作效率。
在一种可能的实现方式中,所述采集环境包括:所述基准光环境或非基准光环境。
本申请实施例的技术方案中,基准光环境包括光照强度为0-1000Lux的正常光环境,非基准光环境包括光照强度大于等于1000Lux的强光环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境包括:根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像确定所述第一指纹图像的采集环境包括:根据所述第一指纹图像和预存的所述基准图像的边界像素值变化趋势确定所述第一指纹图像的采集环境。
本申请实施例的技术方案中,指纹识别装置不需要在有背光和没有背光的情况下各采集一张图片进行比较确定环境光从而根据环境光判断指纹的采集环境,而是直接将采集到的指纹图像与基准图像的特征进行对比即可判断采集环境,简化了采集指纹图像与判断采集环境的步骤,提升了指纹识别装置的工作效率。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
应理解,区域中所述像素值差值的平均数为第一指纹图像的一个区域中第一指纹图像的像素值与基准图像对应区域的像素值的差值的平均数,即第一指纹图像的一个区域的像素值差值的平均数。
本申请实施例的技术方案中,将采集到的指纹图像分成若干个区域进行处理,相应地,基准图像也被分成若干个区域与指纹图像的若干个区域进行 对比,将指纹图像细化成不同区域,统计各个区域每个像素点与对应的基准图像的像素点的像素值差值的平均值,再判断区域平均值大于第一预设平均数的区域数量是否大于预设区域数量,能够更加全面、合理地判断指纹图像的整体情况。
应理解,所述第一预设平均数为判断每个所述区域的像素值差值平均数的阈值,与所述区域的数量呈正相关。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境包括:根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
本申请实施例的技术方案中,通过采集到的指纹图像的自身像素数据和指纹图像与基准图像的比较数据两种参数结合,能够更加准确判断采集环境,进一步提升指纹识别装置对采集环境的判断能力。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述第一指纹图像的采集环境为所述非基准光环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述像素值差值的平均数大于第二预设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
在一种可能的实现方式中,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
应理解,所述第二预设平均数为判断所述指纹图像与所述基准图像全图像素值差值平均数的阈值,可根据像素数目进行配置。
本申请实施例的技术方案中,在引入指纹图像自身像素数据的情况下,可以不对指纹图像与基准图像进行区域划分,通过统计采集的指纹图像中像素值饱和的像素点的数目占全图像素点的比例,以及指纹图像与基准图像全图的每个像素点的像素值差值的平均数,与预设比值和第二预设平均数进行比较,既避免仅使用单个判断条件进行判断时可能造成的误差,又简化了判断过程,进一步优化指纹制备装置对采集环境的判断能力。
在一种可能的实现方式中,所述方法还包括:根据所述非基准光环境调整所述采样参数。
本申请实施例的技术方案中,在非基准光环境下,完成指纹识别后对采样参数进行调整优化,使得后续采样使用调整后的采样参数,进一步避免在非基准光环境下采样参数不当造成的指纹图形不清晰等问题。通过判断采集环境能够动态调整指纹图像的采集参数,能够从后续采集到的指纹图像获中取更多有效的指纹信息,提升指纹识别装置的识别性能。
在一种可能的实现方式中,所述方法还包括:根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
在一种可能的实现方式中,所述方法还包括:根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
在一种可能的实现方式中,所述方法还包括:根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数、所述预设区域数量和所述预设比值。
本申请实施例的技术方案中,在基准光环境下,进行指纹识别后得到对应的指纹识别结果,当指纹图像纹理不清晰,识别不成功时,具有反馈机制,能够根据识别结果,动态调整采集环境的判断参数,即所述第一预设平均数、 所述第二预设平均数、所述预设区域数量和所述预设比值。通过反馈识别结果,自适应调整采集环境的判断参数,能够提升指纹识别装置对采集环境判断的准确性,使指纹识别装置使用对应的处理参数处理指纹图像以获得更多有效的指纹信息。
在一种可能的实现方式中,所述采样参数包括曝光时间、增益参数和曝光区域。
在一种可能的实现方式中,所述根据所述非基准光环境调整所述采样参数包括:根据所述非基准光环境减少曝光时间,和/或减小增益参数。
在一种可能的实现方式中,所述根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量包括:当所述第一指纹图像识别不成功时,下调所述第一预设平均数和/或所述预设区域数量。
在一种可能的实现方式中,所述根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值包括:当所述第一指纹图像识别不成功时,下调所述第二预设平均数和/或所述预设比值。
第二方面,提供一种指纹识别装置,包括:
光学指纹传感器,用于根据采样参数,采集第一指纹图像;
处理单元,用于根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像,根据所述采集环境对应的处理参数处理所述第一指纹图像,根据处理后的所述第一指纹图像进行指纹识别。
在一种可能的实现方式中,所述采集环境包括:所述基准光环境或非基准光环境。
在一种可能的实现方式中,所述处理单元用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
在一种可能的实现方式中,所述处理单元用于:根据所述第一指纹图像和预存的所述基准图像的边界像素值变化趋势确定所述第一指纹图像的采集环境。
在一种可能的实现方式中,所述处理单元用于:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
在一种可能的实现方式中,所述处理单元用于:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
在一种可能的实现方式中,所述处理单元用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
在一种可能的实现方式中,所述处理单元用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述像素值差值的平均数大于第二预设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
在一种可能的实现方式中,所述处理单元用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
在一种可能的实现方式中,所述处理单元还用于:根据所述非基准光环境调整所述采样参数。
在一种可能的实现方式中,所述处理单元还用于:根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
在一种可能的实现方式中,所述处理单元还用于:根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
在一种可能的实现方式中,所述采样参数包括曝光时间、增益参数和曝光区域。
在一种可能的实现方式中,所述处理单元还用于:根据所述非基准光环境减少曝光时间,和/或减小增益参数。
在一种可能的实现方式中,当所述第一指纹图像识别不成功时,下调所述第一预设平均数和/或所述预设区域数量。
在一种可能的实现方式中,所述处理单元还用于:当所述第一指纹图像识别不成功时,下调所述第二预设平均数和/或所述预设比值。
第三方面,提供一种电子设备,包括:显示屏,以及第二方面中的任一种可能的实现方式中的指纹识别装置。
图1A和图1B是本申请实施例可以适用的电子设备的示意图。
图2是本申请实施例一种指纹识别方法的示意性流程图。
图3是本申请实施例一种指纹图像的若干区域的示意图。
图4是本申请实施例另一种指纹识别方法的示意性流程图。
图5是本申请实施例又一种指纹识别方法的示意性流程图。
图6是本申请实施例一种指纹识别装置的示意图。
图7是本申请实施例一种电子设备的示意图。
下面将结合附图,对本申请实施例中的技术方案进行描述。
应理解,本申请实施例可以应用于光学指纹***,包括但不限于光学指纹识别***和基于光学指纹成像的产品,本申请实施例仅以光学指纹***为例进行说明,但不应对本申请实施例构成任何限定,本申请实施例同样适用于其他采用光学成像技术的***等。
作为一种常见的应用场景,本申请实施例提供的光学指纹***可以应用在智能手机、平板电脑以及其他具有显示屏的移动终端或者其他电子设备;更具体地,在上述电子设备中,光学指纹模组可以设置在显示屏下方的局部区域或者全部区域,从而形成屏下(Under-display或Under-screen)光学指纹***。或者,所述光学指纹模组也可以部分或者全部集成至所述电子设备的显示屏内部,从而形成屏内(In-display或In-screen)光学指纹***。
屏下光学指纹检测技术使用从设备显示组件的顶面返回的光线来进行指纹感应和其他感应操作。所述返回的光线携带与该顶面接触的物体,例如手指的信息,通过采集和检测该手指返回的光,实现位于显示屏下方的特定光学传感器模块的光学指纹检测。光学传感器模块的设计可以为通过恰当地配置用于采集和检测返回的光的光学元件来实现期望的光学成像。
图1A是本申请实施例一种电子设备的平面示意图。该电子设备可以包括但不限于移动终端(Mobile Terminal)、移动电话(Mobile Telephone)、用户设备(User Equipment,UE)、手机(handset)及便携设备(portable equipment)等。如图1A所示,电子设备10包括显示屏120和指纹识别装置130。其中,指 纹识别装置130设置在所述显示屏120下方的局部区域。指纹识别装置130包括光学指纹传感器,所述光学指纹传感器包括具有多个光学感应单元131(也称为像素、感光像素、像素单元等)的感应阵列133。所述感应阵列133所在区域或者其感应区域为指纹识别装置130的指纹识别区域103。如图1A所示,所述指纹识别区域103位于所述显示屏120的显示区域之中。在一种替代的实现方式中,指纹识别装置130设置在其他位置,比如设置在所述显示屏120的侧面或者所述电子设备10的边缘非透光区域,并通过光路设计来将来自所述显示屏120的至少部分显示区域的光信号导引到指纹识别装置130,从而使得指纹识别区域103实际上位于所述显示屏120的显示区域。
应理解,指纹识别区域103的面积可以与指纹识别装置130的感应阵列133的面积不同,例如通过透镜成像的光路设计、反射式折叠光路设计或者其他光线会聚或者反射等光路设计,使得指纹识别装置130的指纹识别区域103的面积大于指纹识别装置130的感应阵列133的面积。在其他替代的实现方式中,如果采用例如光线准直的方式进行光路引导,指纹识别装置130的指纹识别区域103也可以设计成与指纹识别装置130的感应阵列133的面积基本一致。
因此,用户在需要对所述电子设备10进行解锁或者其他指纹验证的时候,只需要将手指按压在位于所述显示屏120的指纹识别区域103,便可以实现指纹输入。由于指纹检测可以在屏内实现,因此采用上述结构的电子设备10无需其正面专门预留空间来设置指纹按键(比如Home键),从而可以采用全面屏方案,即所述显示屏120的显示区域可以基本扩展到整个电子设备10的正面。
应理解,在具体实现上,所述电子设备10还可以包括透明保护盖板,所述盖板可以为玻璃盖板或者蓝宝石盖板,其位于所述显示屏120的上方并覆盖所述电子设备10的正面。因此,本申请实施例中,所谓的手指按压在所述显示屏120实际上是指按压在所述显示屏120上方的盖板或者覆盖所述盖板的保护层表面。
可选地,如图1B所示,所述显示屏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,指纹识别装置130可以利用所述OLED显示屏120位于所述指纹识别区域 103的显示单元(即OLED光源)作为光学指纹检测的激励光源。当手指140按压在所述指纹识别区域103时,所述显示屏120向所述指纹识别区域103上方的手指140发出一束光111,光111在手指140的表面发生反射形成反射光或者经过所述手指140内部散射而形成散射光。在相关专利申请中,为便于描述,也将上述反射光和散射光统称为反射光。由于指纹的脊(ridge)141与谷(valley)142对于光的反射能力不同,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,反射光经过光学组件后,被指纹识别装置130中的感应阵列133接收并转换为相应的电信号,即指纹检测信号。基于所述指纹检测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,从而在所述电子设备10中实现光学指纹检测功能。
可选地,指纹识别装置130也可以采用内置光源或者外置光源来提供用于进行指纹检测的光信号。在这种情况下,指纹识别装置130可以适用于非自发光显示屏,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检测,所述电子设备10的光学指纹***还可以包括用于光学指纹检测的激励光源,所述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,其可以设置在所述液晶显示屏的背光模组下方或者设置在所述电子设备10的保护盖板下方的边缘区域,而指纹识别装置130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指纹检测光可以到达指纹识别装置130;或者,指纹识别装置130也可以设置在所述背光模组下方,且所述背光模组通过对扩散片、增亮片、反射片等膜层进行开孔或者其他光学设计以允许指纹检测光穿过液晶面板和背光模组并到达指纹识别装置130。当采用指纹识别装置130采用内置光源或者外置光源来提供用于进行指纹检测的光信号时,其检测原理与上面描述内容是一致的。
所述电子设备10还可以包括电路板,电路板设置在指纹识别装置130的下方。指纹识别装置130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130可以通过电路板实现与其他***电路或者电子设备10的其他元件的电性互连和信号传输。例如,指纹识别装置130可以通过电路板接收电子设备10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130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。
在实际的光学指纹检测过程中,由于待识别的指纹所在的光环境有强度不可控的环境光,会影响经过指纹反射的反射光,当环境光较强时,容易超过光学指纹传感器中像素单元的量程,从而失去指纹纹理信息,影响指纹识别装置的识别性能。针对上述强光场景,可以在指纹传感器中额外设置强光感应单元,根据强光感应单元接收的光信号判断当前是否处于强光场景,从而调整指纹识别装置在采集指纹信息时的工作条件或在采集指纹信息后的成像条件等,但额外增设的强光感应单元,会增加指纹识别装置的成本。另外指纹识别装置可以在显示屏发光和不发光的情况下各采集一张指纹图片,根据两张图片的指纹清晰程度判断是否处于强光场景,但此种方案需要采集两张图片才能判断环境光的强弱情况,导致指纹识别装置的响应速度比较慢。
有鉴于此,本申请实施例提出了一种指纹识别的方法,通过预存正常环境光场景下的基准图像,只需要采集一张图片即可与预存的基准图像比较进行强光场景的判断,通过指纹识别结果反馈机制能够不断动态调整强光场景的判断参数、在采集待识别指纹的指纹图像时的采样参数,进而减少环境光对指纹检测过程中指纹采集的影响。
图2是本申请实施例的一种指纹识别方法的示意性流程图。
在S201中,根据采样参数,采集第一指纹图像。
具体地,指纹识别装置根据初始的采样参数,使用默认采样参数进行采样,获取指纹图像,采样参数包括曝光时间、曝光区域、增益参数等。
在S202中,根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像。
具体地,在指纹识别装置出厂时预存基准图像,根据采集到的第一指纹图像与预存的基准图像进行对比处理,判断第一指纹图像的采集环境。应理解,所述基准图像可以是指纹图像,也可以是基准光环境下模拟手指按压的模拟图像,例如,基准光环境下肉色按压模拟图像,即采用与真实手指接近的肉色模拟手指获取基准图像。
可选地,采集环境包括基准光环境和非基准光环境。
示例性地,基准光环境包括光照强度为0-1000Lux的正常光环境,非基准光环境包括光照强度大于等于1000Lux的强光环境。
在S203中,根据所述采集环境对应的处理参数处理所述第一指纹图像。
具体地,基准光环境与非基准光环境下指纹识别装置使用不同的指纹识 别处理参数,指纹识别装置在对采集环境进行判断后根据与采集环境对应的处理参数对指纹图像进行处理。处理参数可以是指纹识别装置中预设的,也可以是根据采集环境动态调整的,本申请实施例对此不做限定。
示例性地,处理参数包括像素值量化尺度、光学指纹传感器的本底噪声等。例如,在非基准光环境下,使用非基准光下像素值的量化尺度提取指纹纹理以获得更加清晰的指纹图像。
像素值量化尺度指将不同曝光时间,不同增益参数采集的数据,调整到同一个曝光时间,同一个增益参数对应的数据的过程中使用的参数。例如,默认采样时曝光时间为100μs,非基准光环境采样时曝光时间为50μs,非基准光环境下的采样数据需乘以像素值量化尺度,即乘以2,再与默认条件下采样的数据进行比较。光学指纹传感器使用不同的采集参数来采集数据时,其本底噪声(sensor base)不同,因此需要减去采用不同采集参数时对应的本底噪声,才能得到光学指纹传感器实际的感应值。
在S204中,根据处理后的所述第一指纹图像进行指纹识别。
在本实施例中,通过预存基准光环境下的基准图像,在不增加额外的强光感应单元的情况下,从采集到的指纹图像中提取采集环境的光线特征与预存的基准图像的光线特征进行对比处理,判断所述指纹图像的采集环境,根据采集环境对应的处理参数处理所述指纹图像。由于预存了基准图像,指纹识别装置仅采集一张图像就能实现指纹的采集环境的快速判断,节省了采集指纹图像以及判断指纹采集环境的时间,提升了指纹采集装置的工作效率。通过判断采集环境能够动态调整指纹图像的处理参数,提升指纹识别装置的识别性能。
可选地,在S202中,根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
具体地,在指纹识别装置采集到第一指纹图像后,统计第一指纹图像的每个像素点的像素值,由于已经预存了基准图像,指纹识别装置只需提取基准图像的像素值信息计算与第一指纹图像的像素值差值,即可通过像素值差值的情况判断第一指纹图像的采集环境。例如,所述像素值差值的平均数大于预设值时,判断采集环境为非基准环境。
可选地,在S202中,根据所述第一指纹图像和预存的所述基准图像的边界像素值变化趋势确定所述第一指纹图像的采集环境。
具体地,在指纹识别装置采集到第一指纹图像后,统计第一指纹图像的边界像素点的像素值变化趋势,提取基准图像相应的边界像素点的像素值变化趋势,通过边界像素值的变化趋势判断第一指纹图像的采集环境。例如,第一指纹图像的边界像素值变化趋势大于基准图像的边界像素值变化趋势,判断采集环境为非基准环境。
在本实施例中,指纹识别装置不需要在有背光和没有背光的情况下各采集一张图片进行比较确定环境光从而根据环境光判断指纹的采集环境,而是直接将采集到的指纹图像与基准图像的特征进行对比即可判断采集环境,简化了采集指纹图像与判断采集环境的步骤,提升了指纹识别装置的工作效率。
可选地,在S202中,当所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
可选地,在S202中,当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
具体地,将第一指纹图像300分成若干个区域,如图3所示。将第一指纹图像每个像素点的像素值与基准图像对应的每个像素点的像素值做差后,统计每个区域的像素值差值平均值,将每个区域的差值平均值与第一预设平均数比较后,统计差值平均值大于第一预设平均数的区域的数量,只有当区域数量大于预设数量时,判断采集环境为非基准光环境;其他情况均为基准光环境。
应理解,所述第一预设平均数为判断每个所述区域的像素值差值平均数的阈值,与所述区域的数量呈正相关。
应理解,所述预设数量根据可根据所述区域数量、第一预设平均数进行配置。
在本实施例中,将采集到的指纹图像细化成若干个区域进行判断,使得判断结果能够更全面、平均地反应第一指纹图像全图的整体环境光情况。
可选地,在S202中,根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
具体地,指纹识别装置在采集到第一指纹图像后,统计整个第一指纹图 像中给像素值大于一定预设值或像素值饱和的像素点的数量,结合第一指纹图像与基准图像的像素值差值,若这些像素点的数量大于预设像素点数量,且像素值差值大于预设差值,判断采集环境为非基准环境。
可选地,当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述第一指纹图像的采集环境为所述非基准光环境。
可选地,当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
本实施例中,通过采集到的指纹图像的自身像素数据和指纹图像与基准图像的比较数据两种参数结合,能够更加准确判断采集环境,进一步提升指纹识别装置对采集环境的判断能力。
可选地,在S202中,当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述像素值差值的平均数大于第二预设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
可选地,在S202中,当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
具体地,指纹识别装置采集第一指纹图像后,统计第一指纹图像中像素值已经饱和的像素点占全全图像素点的比例,计算第一指纹图像与基准图像全图的每个像素点的像素值差值的平均数,只有当所述比例大于预设比值且所述平均数大于第二预设平均数时,判断采集环境为非基准光环境;其他情况均为基准光环境。
应理解,所述第二预设平均数为判断所述指纹图像与所述基准图像全图像素值差值平均数的阈值。
应理解,在引入指纹图像自身像素数据的情况下,可以结合对指纹图像进行分区的方法,例如,利用指纹图像的多个区域中像素值饱和的像素点的 数目大于预设数目的区域数量与预设数量的比较进行采集环境的判断;也可以不对指纹图像与基准图像进行区域划分,通过统计采集的指纹图像中像素值饱和的像素点的数目占全图像素点的比例,以及指纹图像与基准图像全图的每个像素点的像素值差值的平均数,与预设比值和第二预设平均数进行比较即可判断采集环境。
在本实施例中,能够通过两种角度的判断参数综合判断采集环境,避免仅使用单个判断条件进行判断时可能造成的误差,简化了判断过程,进一步优化指纹制备装置对采集环境的判断能力。
可选地,如图4所示,是本申请实施例的另一指纹识别方法的示意性流程图,所述指纹识别方法还包括:
S205,根据所述非基准光环境调整所述采样参数。
具体地,当指纹识别装置根据非基准光环境对应的处理参数处理指纹图像并进行指纹识别后,调整采样参数。
例如,在判断为非基准光环境并进行指纹识别后,减小指纹识别装置中光学指纹传感器的曝光时间,使得后续采样的曝光时间缩短,减少非基准光环境,如强光环境下,采样过饱和导致的指纹纹理不清晰的情况,在非基准光环境下指纹识别装置的后续采样的指纹图像的有效面积增加。
又例如,在判断为非基准光环境并进行指纹识别后,减小光学指纹传感器的灵敏度增益,灵敏度为光学指纹传感器单位光照下的光通感应量,在非基准光环境下减小灵敏度增益,降低光学指纹传感器的感应量,能够降低后续采样图像过饱和的概率,使采集到的指纹图像更加清晰,具有更多有效的指纹信息。
再例如,在判断为非基准光环境并进行指纹识别后,选择非基准光环境的区域作为曝光区域,针对性地调整曝光区域的曝光时间以及增益参数,使得采集到的指纹图像更加清晰具备更多细节。
可选地,如图5所示,是本申请实施的又一指纹识别方法的示意性流程图,所述方法还包括:
S206,根据处理后的所述第一指纹图像对应的识别结果,调整所述采集环境的判断依据。
具体地,根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
例如,当指纹识别装置根据基准光环境对应的处理参数处理指纹图像并进行指纹识别后,得到指纹识别结果,当指纹识别不成功时,说明虽然判定为正常光环境,但指纹纹理仍不清晰,需调整采集环境的判断参数,如下调所述第一预设平均数和/或所述预设区域数量,使采集环境更容易被判定为非基准光环境,使用非基准光环境对应的处理参数处理指纹图像避免处理参数不当造成的指纹图像细节丢失。又例如,当指纹识别成功时,上调所述第一预设平均数和/或所述预设区域数量,或维持所述第一预设平均数和/或所述预设区域数量不变。
具体地,根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
例如,当指纹识别装置根据基准光环境对应的处理参数处理指纹图像并进行指纹识别后,得到指纹识别结果,当指纹识别不成功时,下调所述第二预设平均数和/或所述预设比值,使采集环境更容易被判定为非基准光环境,使用非基准光环境对应的处理参数处理指纹图像。
又例如,当指纹识别成功时,上调所述第二预设平均数和/或所述预设比值,或维持所述第二预设平均数和/或所述预设比值不变。
在本实施例中,指纹识别装置内部具有自反馈机制,能够根据指纹识别结果动态改变采集环境的判断参数,使得指纹识别装置能够不断自适应调整对采集环境的判断,在提升指采集环境判断的准确性的同时,通过更加灵活准确的采集环境判断使得指纹识别装置使用更加合理的处理参数处理指纹识别图像,提升指纹识别装置的工作效率。
如图6所示,为本申请实施例提供的一种指纹识别装置600的示意图,指纹识别装置包括:
光学指纹传感器601,用于根据采样参数,采集第一指纹图像;
处理单元602,用于根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像,根据所述采集环境对应的处理参数处理所述第一指纹图像,根据处理后的所述第一指纹图像进行指纹识别。
可选地,采集环境包括基准光环境和非基准光环境。
可选地,处理参数包括像素值量化尺度、光学指纹传感器的本底噪声。例如,在非基准光环境下,处理单元602使用非基准光下像素值的量化尺度 提取指纹纹理以获得更加清晰的指纹图像。
应理解,处理单元602的功能可以由集成于指纹识别芯片内的处理器或处理模块执行,也可以由包括指纹识别装置的终端设备内的处理器或处理模块执行,本申请实施例对此不做限定。
处理器可以是中央处理单元(Central Processing Unit,CPU),该处理器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。
本申请实施例中,指纹识别装置只需采集一张指纹图像,处理单元602通过提取预存的基准图像与采集到的指纹图像进行对比即可判断指纹图像的采集环境,节省了采集指纹图像以及判断指纹采集环境的时间,提升了指纹采集装置的工作效率。
在一种可能的实施方式中,所述处理单元602用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
具体地,处理单元602能够提取预存于指纹识别装置内的基准图像,在光学指纹传感器601采集第一指纹图像后,提取第一指纹图像的像素值特征,与基准图像的相应像素值做差得到像素值差值,根据像素值差值进行采集环境判断。
在一种可能的实施方式中,所述处理单元602用于:根据所述第一指纹图像和预存的所述基准图像的边界像素值变化趋势确定所述第一指纹图像的采集环境。
在一种可能的实施方式中,所述处理单元602用于:当所述第一指纹图像中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
在一种可能的实施方式中,所述处理单元602用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
在一种可能的实施方式中,所述处理单元602用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大 于预设比值,且所述像素值差值的平均数大于第二预设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
在一种可能的实施方式中,所述处理单元602用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
在一种可能的实施方式中,所述处理单元602还用于:根据所述非基准光环境调整所述采样参数。
处理单元602在非基准光环境下识别指纹图像后调整采样参数,控制光学指纹传感器601在后续采样中使用调整后的参数采样,优化采样过程,避免了由于采样参数合适造成的指纹图像纹理不清晰等问题。
在一种可能的实施方式中,所述处理单元602还用于:根据所述识别结果调整所述采集环境的判断参数。
处理单元602在非基准光环境下识别指纹图像后调整采集环境的判断参数,在判断为基准光环境并进行指纹识别后得到识别结果,若识别不成功,调整判断参数使采集环境更易被判断成非基准光环境,避免因判断参数不当造成的判断误差,使得指纹识别装置能够通过识别结果不断自适应调节判断参数,提升判断采集环境的准确性,从而保证指纹识别装置采用更合理的对应的处理参数处理指纹识别图像,提升纹识别装置的工作效率。
例如,根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
具体地,当采集环境被判断为基准光环境进行指纹识别后,若识别不成功,下调所述第一预设平均数和/或所述预设区域数量;若识别成功,上调所述第一预设平均数和/或所述预设区域数量,或维持所述第一预设平均数和/或所述预设区域数量不变。
又例如,根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
具体地,当采集环境被判断为基准光环境进行指纹识别后,若识别不成功,下调所述第二预设平均数和/或所述预设比值;若识别成功,上调所述第二预设平均数和/或所述预设比值,或维持所述第二预设平均数和/或所述预设比值不变。
如图7所示,本申请实施例还提供一种电子设备700,包括:
显示屏701,
以及所述指纹识别装置600。
应理解,显示屏701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。
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***、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***,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 (31)
- 一种指纹识别方法,其特征在于,应用于指纹识别装置,所述方法包括:根据采样参数,采集第一指纹图像;根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像;根据所述采集环境对应的处理参数处理所述第一指纹图像;根据处理后的所述第一指纹图像进行指纹识别。
- 根据权利要求1所述的方法,其特征在于,所述采集环境包括:所述基准光环境或非基准光环境。
- 根据权利要求1或2所述的方法,其特征在于,所述根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境包括:根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
- 根据权利要求3所述的方法,其特征在于,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
- 根据权利要求3所述的方法,其特征在于,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
- 根据权利要求1或2所述的方法,其特征在于,所述根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境包括:根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
- 根据权利要求6所述的方法,其特征在于,所述根据所述第一指纹 图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述像素值差值的平均数大于第二预设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
- 根据权利要求6所述的方法,其特征在于,所述根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境包括:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
- 根据权利要求4或7所述的方法,其特征在于,所述方法还包括:根据所述非基准光环境调整所述采样参数。
- 根据权利要求5所述的方法,其特征在于,所述方法还包括:根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
- 根据权利要求8所述的方法,其特征在于,所述方法还包括:根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
- 根据权利要求1所述的方法,其特征在于,所述采样参数包括曝光时间、增益参数和曝光区域。
- 根据权利要求9所述的方法,其特征在于,所述根据所述非基准光环境调整所述采样参数包括:根据所述非基准光环境减少曝光时间,和/或减小增益参数。
- 根据权利要求10所述的方法,其特征在于,所述根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量包括:当所述第一指纹图像识别不成功时,下调所述第一预设平均数和/或所述预设区域数量。
- 根据权利要求11所述的方法,其特征在于,所述根据处理后的所 述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值包括:当所述第一指纹图像识别不成功时,下调所述第二预设平均数和/或所述预设比值。
- 一种指纹识别装置,其特征在于,包括:光学指纹传感器,用于根据采样参数,采集第一指纹图像;处理单元,用于根据所述第一指纹图像和预存的基准图像确定所述第一指纹图像的采集环境,所述基准图像为基准光环境下获取的指纹图像,根据所述采集环境对应的处理参数处理所述第一指纹图像,根据处理后的所述第一指纹图像进行指纹识别。
- 根据权利要求16所述的装置,其特征在于,所述采集环境包括:所述基准光环境或非基准光环境。
- 根据权利要求16或17所述的装置,其特征在于,所述处理单元用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值确定所述第一指纹图像的采集环境。
- 根据权利要求18所述的装置,其特征在于,所述处理单元用于:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量大于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述非基准光环境。
- 根据权利要求18所述的装置,其特征在于,所述处理单元用于:当所述第一指纹图像的多个区域中所述像素值差值的平均数大于第一预设平均数的区域数量小于或等于预设区域数量时,确定所述指纹图像所在的指纹识别环境为所述基准光环境。
- 根据权利要求16或17所述的装置,其特征在于,所述处理单元用于:根据所述第一指纹图像和预存的所述基准图像的像素值差值与所述第一指纹图像的像素值确定所述第一指纹图像的采集环境。
- 根据权利要求21所述的装置,其特征在于,所述处理单元用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值大于预设比值,且所述像素值差值的平均数大于第二预 设平均数时,确定所述第一指纹图像的采集环境为所述非基准光环境。
- 根据权利要求21所述的装置,其特征在于,所述处理单元用于:当所述第一指纹图像中所述像素值饱和的像素数目与所述第一指纹图像的像素数目的比值小于或等于预设比值,和/或所述像素值差值的平均数小于或等于第二预设平均数时,确定所述第一指纹图像的采集环境为所述基准光环境。
- 根据权利要求19或22所述的装置,其特征在于,所述处理单元还用于:根据所述非基准光环境调整所述采样参数。
- 根据权利要求20所述的装置,其特征在于,所述处理单元还用于:根据处理后的所述第一指纹图像对应的识别结果,调整所述第一预设平均数和所述预设区域数量。
- 根据权利要求23所述的装置,其特征在于,所述处理单元还用于:根据处理后的所述第一指纹图像对应的识别结果,调整所述第二预设平均数和所述预设比值。
- 根据权利要求16所述的装置,其特征在于,所述采样参数包括曝光时间、增益参数和曝光区域。
- 根据权利要求24所述的装置,其特征在于,所述处理单元还用于:根据所述非基准光环境减少曝光时间,和/或减小增益参数。
- 根据权利要求25所述的装置,其特征在于,所述处理单元还用于:当所述第一指纹图像识别不成功时,下调所述第一预设平均数和/或所述预设区域数量。
- 根据权利要求26所述的装置,其特征在于,所述处理单元还用于:当所述第一指纹图像识别不成功时,下调所述第二预设平均数和/或所述预设比值。
- 一种电子设备,其特征在于,包括:显示屏;以及根据权利要求16至30中任一项所述的指纹识别装置。
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140286544A1 (en) * | 2013-03-22 | 2014-09-25 | Suprema Inc. | Method and apparatus for optical fingerprint recognition using multiple exposure |
CN109241859A (zh) * | 2018-08-13 | 2019-01-18 | Oppo广东移动通信有限公司 | 指纹识别方法及相关产品 |
CN109711255A (zh) * | 2018-11-26 | 2019-05-03 | Oppo广东移动通信有限公司 | 指纹采集方法及相关装置 |
CN111801683A (zh) * | 2020-04-08 | 2020-10-20 | 深圳市汇顶科技股份有限公司 | 指纹识别的方法、装置和电子设备 |
CN112507917A (zh) * | 2020-12-16 | 2021-03-16 | 北京集创北方科技股份有限公司 | 一种光学指纹识别方法、装置、电子设备及存储介质 |
CN112528888A (zh) * | 2020-12-16 | 2021-03-19 | 北京集创北方科技股份有限公司 | 一种光学指纹采集方法、装置、电子设备及存储介质 |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107656665A (zh) * | 2016-07-25 | 2018-02-02 | 印象认知(北京)科技有限公司 | 基于显示屏的指纹采集控制方法、装置及电子设备 |
US10354116B2 (en) * | 2017-07-06 | 2019-07-16 | Synaptics Incorporated | Optical fingerprint sensor with scattered light image detection |
EP3462374A1 (en) * | 2017-08-18 | 2019-04-03 | Shenzhen Goodix Technology Co., Ltd. | Fingerprint image acquisition method and device, and terminal device |
CN109685032A (zh) * | 2018-12-29 | 2019-04-26 | 联想(北京)有限公司 | 图像处理方法、装置、电子设备以及存储介质 |
CN109901754B (zh) * | 2019-02-20 | 2021-04-13 | Oppo广东移动通信有限公司 | 数据自校准方法及相关装置 |
US11176347B2 (en) * | 2019-06-14 | 2021-11-16 | Analog Devices International Unlimited Company | Fingerprint-on-display recognition |
KR20210025752A (ko) * | 2019-08-27 | 2021-03-10 | 삼성디스플레이 주식회사 | 지문 센싱 방법, 지문 센서 및 이를 포함하는 표시 장치 |
CN112101194A (zh) * | 2020-01-21 | 2020-12-18 | 神盾股份有限公司 | 电子装置及其操作方法 |
-
2021
- 2021-04-09 EP EP21916669.1A patent/EP4092567A4/en active Pending
- 2021-04-09 WO PCT/CN2021/086254 patent/WO2022213382A1/zh unknown
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-
2022
- 2022-07-19 US US17/867,824 patent/US20220351541A1/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140286544A1 (en) * | 2013-03-22 | 2014-09-25 | Suprema Inc. | Method and apparatus for optical fingerprint recognition using multiple exposure |
CN109241859A (zh) * | 2018-08-13 | 2019-01-18 | Oppo广东移动通信有限公司 | 指纹识别方法及相关产品 |
CN109711255A (zh) * | 2018-11-26 | 2019-05-03 | Oppo广东移动通信有限公司 | 指纹采集方法及相关装置 |
CN111801683A (zh) * | 2020-04-08 | 2020-10-20 | 深圳市汇顶科技股份有限公司 | 指纹识别的方法、装置和电子设备 |
CN112507917A (zh) * | 2020-12-16 | 2021-03-16 | 北京集创北方科技股份有限公司 | 一种光学指纹识别方法、装置、电子设备及存储介质 |
CN112528888A (zh) * | 2020-12-16 | 2021-03-19 | 北京集创北方科技股份有限公司 | 一种光学指纹采集方法、装置、电子设备及存储介质 |
Non-Patent Citations (1)
Title |
---|
See also references of EP4092567A4 * |
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EP4092567A4 (en) | 2023-05-03 |
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