Parameter detection method, device, electronic equipment and computer storage medium

Abstract

The present application discloses a parameter detection method, apparatus, electronic device, and computer storage medium. In the present application, a target image of a screen to be tested is obtained at different preset exposure times; a target grayscale value of the target image is determined, and a brightness-to-grayscale mapping strategy corresponding to the different preset exposure times is obtained; the target grayscale value is substituted into the brightness-to-grayscale mapping strategy for mapping, obtaining a target brightness value corresponding to the target grayscale value; and a display parameter detection result of the screen to be tested is determined based on the target brightness value. The present application can improve the accuracy of the display parameter detection results.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and specifically to a parameter detection method, device, electronic device and computer storage medium. Background Art

[0002] With the development of science and technology, electronic equipment is becoming more and more popular among users, and the application fields of electronic equipment are becoming wider and wider.

[0003] Before or during the use of electronic devices, the brightness and chromaticity of the electronic devices are tested to ensure the display quality of the electronic devices. However, the accuracy of the current methods for testing the brightness and chromaticity of electronic devices is relatively low. Summary of the Invention

[0004] The embodiments of the present application provide a parameter detection method, device, electronic device, and computer storage medium, which can solve the technical problem of low accuracy of brightness and chromaticity detection methods.

[0005] The present invention provides a parameter detection method, including:

[0006] Obtain target images of the screen to be tested under different preset exposure times;

[0007] Determine the target grayscale value of the target image and obtain the brightness-to-grayscale mapping strategies corresponding to the different preset exposure times;

[0008] Substituting the target grayscale value into the brightness-to-grayscale mapping strategy for mapping, and obtaining the target brightness value corresponding to the target grayscale value;

[0009] According to the target brightness value, the display parameter detection result of the screen to be tested is determined.

[0010] Accordingly, an embodiment of the present application provides a parameter detection device, comprising:

[0011] An image acquisition module is used to acquire target images of the screen to be tested under different preset exposure times;

[0012] A first determination module is used to determine the target grayscale value of the target image and obtain the brightness-to-grayscale mapping strategies corresponding to the different preset exposure times;

[0013] A grayscale mapping module is used to substitute the target grayscale value into the brightness-to-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value;

[0014] The second determining module is used to determine the display parameter detection result of the screen to be tested according to the target brightness value.

[0015] In addition, an embodiment of the present application also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is used to run the computer program in the memory to implement the parameter detection method provided in the embodiment of the present application.

[0016] In addition, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. The computer program is suitable for loading by a processor to execute any parameter detection method provided in the embodiment of the present application.

[0017] In addition, an embodiment of the present application also provides a computer program product, including a computer program, which implements any parameter detection method provided in the embodiment of the present application when executed by a processor.

[0018] In an embodiment of the present application, a target image of the screen to be tested under different preset exposure times is obtained; a target grayscale value of the target image is determined, and a brightness-grayscale mapping strategy corresponding to the different preset exposure times is obtained; the target grayscale value is substituted into the brightness-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value; based on the target brightness value, a display parameter detection result of the screen to be tested is determined, and the target grayscale values ​​of the target images under different preset exposure times are mapped through the brightness-grayscale mapping strategy with different preset exposure times to obtain multiple target brightness values, so that the display parameter detection result of the screen to be tested can be determined based on the multiple target brightness values, thereby improving the accuracy of the display parameter detection result. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 Schematic diagram of the process of parameter detection method provided in the embodiment of the present application;

[0021] Figure 2 is a schematic diagram of a method for obtaining a calibration coefficient provided in an embodiment of the present application;

[0022] Figure 3 Schematic diagram of a brightness-grayscale mapping curve provided in an embodiment of the present application;

[0023] Figure 4 Schematic diagram of a method for obtaining a brightness-grayscale mapping function provided in an embodiment of the present application;

[0024] Figure 5Schematic diagram of the brightness-to-grayscale mapping function provided in an embodiment of the present application;

[0025] Figure 6 This is a flow chart of another parameter detection method provided in an embodiment of the present application;

[0026] Figure 7 Schematic diagram of the structure of the parameter detection device provided in the embodiment of the present application;

[0027] Figure 8 is a structural diagram of an electronic device provided in an embodiment of the present application;

[0028] Figure 9 It is a structural diagram of another electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0030] The embodiments of the present application provide a parameter detection method, device, electronic device, and computer storage medium. The parameter detection device can be integrated into an electronic device, which can be a server, a terminal, or other device.

[0031] Among them, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), as well as big data and artificial intelligence platforms.

[0032] The terminal may be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, etc., but is not limited thereto. The terminal and the server may be connected directly or indirectly via wired or wireless communication, and this application does not impose any restrictions thereon.

[0033] In addition, the term "a plurality of" in the embodiments of the present application refers to two or more than two. The terms "first" and "second" in the embodiments of the present application are used to distinguish descriptions and should not be understood to imply relative importance.

[0034] It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments.

[0035] In this embodiment, the description will be made from the perspective of the parameter detection device. In order to facilitate the description of the parameter detection method of the present application, the parameter detection device will be integrated into the terminal for detailed description, that is, the terminal will be used as the execution subject for detailed description.

[0036] See also Figure 1 , Figure 1 : is a flow chart of a parameter detection method provided in an embodiment of the present application. The parameter detection method may include:

[0037] S101 : Acquire target images of a screen to be tested at different preset exposure times.

[0038] The exposure time refers to the light-sensitive time of the image sensor, and different preset exposure times refer to multiple pre-set exposure times.

[0039] The target image is an image obtained by photographing the screen to be tested. When photographing the screen to be tested, the display content of the screen to be tested can be preset content or randomly displayed content, which is not limited in the embodiment of the present application.

[0040] The terminal can use its own camera to obtain target images of the screen under test at different preset exposure times. Alternatively, the terminal can use the camera of another terminal to obtain target images of the screen under test at different preset exposure times, and the other terminal can then send the target images to the terminal. The method for the terminal to obtain the target images can be selected based on actual circumstances and is not limited in this embodiment of the present application.

[0041] A camera may include an imaging lens and an image sensor.

[0042] S102: Determine a target grayscale value of a target image, and obtain brightness-to-grayscale mapping strategies corresponding to different preset exposure times.

[0043] The target grayscale value may refer to the grayscale value of each pixel on the target image, or may refer to the grayscale value of each pixel on the screen to be tested.

[0044] If the target image is a color image, the terminal can first convert the target image into a grayscale image, and then determine the target grayscale value of the target image based on the grayscale image. If the target image is a grayscale image, the terminal can directly determine the target grayscale value of the target image based on the target image.

[0045] The method for converting the target image into a grayscale image can be selected according to the actual situation. For example, the target image can be converted into a grayscale image by a floating point method or an average method, which is not limited in the embodiment of the present application.

[0046] The brightness-to-grayscale mapping strategy refers to the relationship between brightness and grayscale, which can be represented by a mapping table or a mapping function. The brightness-to-grayscale mapping strategy for different preset exposure times can be different. For example, the brightness-to-grayscale mapping strategy for preset exposure time t1 is y1, and the brightness-to-grayscale mapping strategy for preset exposure time t2 is y2, where y1 and y2 are different.

[0047] It should be noted that the brightness in the brightness grayscale mapping strategy can refer to the exposure of the camera, the illuminance of the imaging lens in the camera, or the brightness of the screen to be measured.

[0048] The terminal may first obtain all target images of the screen to be tested under different preset exposure times, and then determine the target grayscale value of the target image. Alternatively, the terminal may filter out the target exposure time from different preset exposure times, and then obtain the target image under the target exposure time, and then determine the target grayscale value of the target image.

[0049] When a target exposure duration is first selected from different preset exposure durations, the target exposure duration may be a randomly selected preset exposure duration, or a pre-set preset exposure duration. For example, the target exposure duration may be the preset exposure duration t, or the preset exposure duration t / 16.

[0050] When the target grayscale value refers to the grayscale value of each pixel on the screen to be tested, the process of determining the target grayscale value of the target image can be:

[0051] Get the transformation matrix between the screen to be tested and the camera;

[0052] Perform transformation processing on the target image according to the transformation matrix to obtain a transformed image;

[0053] According to the transformed image, the target grayscale value of the target image is determined.

[0054] Here, transforming the target image according to the transformation matrix may refer to multiplying the transformation matrix and the target image to obtain a transformed image.

[0055] Due to the limitations of the manufacturing process, the screen may have some display problems, such as Mura (Mura refers to unevenness), bad pixels, light leakage or discoloration. If only the grayscale value of each pixel on the target image is obtained, the grayscale value of each pixel on the target image cannot be matched one by one with the brightness value of each pixel on the screen to be tested, so that it is impossible to judge whether there is a problem with each pixel on the screen to be tested based on the brightness value of each pixel on the screen to be tested. Therefore, in an embodiment of the present application, the target image is transformed by a transformation matrix to obtain a transformed image, so that the target grayscale value of each pixel on the screen to be tested can be determined based on the transformed image, so that the target brightness value of each pixel on the screen to be tested can be determined based on the target grayscale value of each pixel on the screen to be tested, so that it is possible to judge whether there is a problem with each pixel on the screen to be tested based on the target brightness value of each pixel on the screen to be tested.

[0056] Furthermore, since the target brightness value of each pixel on the screen to be tested can be obtained, various problems on the screen to be tested can be digitally archived and the extent of the problems can be quantified.

[0057] Optionally, the process of determining the target grayscale value of the target image according to the transformed image may be:

[0058] Obtain the number of row pixels and column pixels of the screen to be tested, and obtain the sampling magnification of the transformed image relative to the screen to be tested;

[0059] Dividing the transformed image according to the number of row pixels and column pixels of the screen to be tested to obtain multiple pixel clusters;

[0060] According to the sampling magnification and pixel cluster, the target grayscale value of each pixel on the screen to be tested is determined.

[0061] For example, the number of row pixels of the screen to be tested is a, the number of column pixels is b, and the sampling magnification of the transformed image relative to the screen to be tested is n. Then the transformed image is divided into (a*b) pixel clusters, each pixel cluster contains (n*n) pixels, and each pixel cluster corresponds to a pixel of the screen to be tested. The target grayscale value of the target image can be determined based on the grayscale value of the pixel in each pixel cluster.

[0062] The average grayscale value of each pixel in each pixel cluster can be used as the target grayscale value of each pixel on the screen to be tested. Optionally, in order to further improve the accuracy of the target grayscale value, the average grayscale value of each pixel in each pixel cluster can be determined using a floating point method.

[0063] In some embodiments, in order to more accurately obtain the target grayscale value, the target image is transformed according to the transformation matrix to obtain the transformed image, including:

[0064] Transform the target image according to the transformation matrix to obtain a candidate transformed image;

[0065] Perform linear interpolation on the candidate transformed image to obtain the transformed image.

[0066] Since the target image is transformed according to the transformation matrix, there may be pixels with zero pixel values ​​in the obtained candidate transformed image. Therefore, in order to obtain the target grayscale value more accurately, in an embodiment of the present application, linear interpolation is performed on the candidate transformed image to obtain the transformed image, so that there are no pixels with zero pixel values ​​in the transformed image.

[0067] In other embodiments, obtaining a transformation matrix between the screen to be tested and the camera includes:

[0068] Determine the coordinates of multiple source points of the screen to be tested according to the target image;

[0069] According to the number of pixels of the screen to be tested, determine the coordinates of multiple target points corresponding to the camera;

[0070] According to the source point coordinates and the target point coordinates, the transformation matrix between the screen to be tested and the camera is determined.

[0071] The source point coordinates may be the coordinates of the upper left corner, upper right corner, lower left corner, and lower right corner of the screen to be measured. The number of pixels of the screen to be measured may include the number of row pixels and the number of column pixels of the screen to be measured. The target point coordinates may also be the coordinates of the upper left corner, upper right corner, lower left corner, and lower right corner of the image sensor in the camera.

[0072] According to the number of pixels of the screen to be tested, the process of determining the coordinates of multiple target points corresponding to the camera can be:

[0073] Obtain the sampling rate, and determine the coordinates of the upper left corner of the image sensor in the camera based on the sampling rate and the number of row pixels of the screen to be tested;

[0074] Determine the coordinates of the lower right corner of the image sensor in the camera based on the sampling magnification and the number of column pixels of the screen to be measured;

[0075] The coordinates of the upper right corner of the image sensor in the camera are determined according to the sampling magnification, the number of column pixels and the number of column pixels of the screen to be measured.

[0076] For example, if the number of row pixels of the screen to be tested is a, the number of column pixels is b, and the sampling rate is n, then the coordinates of the upper left corner of the image sensor in the camera are (n*a, 0), the coordinates of the lower right corner of the image sensor in the camera are (0, n*b), the coordinates of the upper right corner of the image sensor in the camera are (n*a, n*b), and the coordinates of the lower left corner of the image sensor in the camera are (0, 0).

[0077] The sampling rate can be determined based on the number of pixels on the screen being measured (the number of pixels can be understood as pixel size), the magnification of the imaging lens in the camera, and the number of pixels on the image sensor in the camera. For example, the number of pixels on the screen being measured can be multiplied by the magnification of the imaging lens, and then divided by the number of pixels on the image sensor. The quotient is then used as the sampling rate. If the quotient is not an integer, it is rounded up to obtain the sampling rate.

[0078] In other embodiments, the process of determining the transformation matrix between the screen to be tested and the camera according to the source point coordinates and the target point coordinates may be:

[0079] According to the source point coordinates, the source point matrix is ​​determined, and according to the target point coordinates, the target point matrix is ​​determined;

[0080] Multiply the source point matrix and the matrix to be solved to obtain the target point matrix;

[0081] According to the source point matrix and the target point matrix, the matrix to be solved is solved to obtain the transformation matrix between the screen to be tested and the camera.

[0082] S103: Substitute the target grayscale value into the brightness-to-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value.

[0083] Since the brightness-grayscale mapping strategies corresponding to different preset exposure times are pre-set, after obtaining the target images with different preset exposure times, the target grayscale values ​​of the target images can be substituted into the brightness-grayscale mapping strategies for mapping processing to obtain the target brightness values ​​corresponding to the target grayscale values. This allows detection of display parameters with a wide dynamic range to be achieved without the need for multiple sets of optical attenuation sheets or multiple detectors, thereby reducing costs.

[0084] Moreover, because different preset exposure times correspond to different brightness-grayscale mapping strategies, the target brightness values ​​obtained according to different brightness-grayscale mapping strategies are more accurate, making the display parameter results of the screen to be tested subsequently determined according to the target brightness values ​​more accurate.

[0085] When the brightness in the brightness-to-grayscale mapping strategy refers to the exposure of the camera, the target grayscale value is substituted into the brightness-to-grayscale mapping strategy for mapping. The process of obtaining the target brightness value corresponding to the target grayscale value can be as follows:

[0086] Substitute the target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain the exposure corresponding to the target grayscale value;

[0087] Determine the illumination on the surface of the imaging lens in the camera based on the exposure;

[0088] According to the illumination of the imaging lens surface in the camera, the target brightness value corresponding to the target grayscale value is determined.

[0089] The exposure can be substituted into the following formula to obtain the illuminance on the imaging lens surface:

[0090]

[0091] EV represents the exposure value, and E represents the illuminance on the imaging lens surface.

[0092] The illuminance on the surface of the imaging lens can be substituted into the following formula to calculate the target brightness value corresponding to the target grayscale value:

[0093]

[0094] k represents the compensation coefficient, z represents the distance from the imaging lens to the screen to be measured, which also represents the shortest focusing distance of the imaging lens, and b represents the target brightness value corresponding to the target grayscale value.

[0095] S104: Determine a display parameter detection result of the screen to be tested according to the target brightness value.

[0096] After obtaining the target brightness value, the terminal can determine the display parameter detection result of the screen to be tested based on the target brightness value. The display parameters may include at least one of brightness, chromaticity and color temperature. The display parameter detection result can be at least one of brightness detection result, chromaticity detection result and color temperature detection result. The color temperature detection result can be determined based on the chromaticity coordinates of the screen to be tested.

[0097] When the terminal selects a target exposure time from different preset exposure times and obtains a target image under the target exposure time, the process of determining the display parameter detection result of the screen to be tested according to the target brightness value may be as follows:

[0098] If the target brightness value meets the preset detection conditions, the display parameter detection result of the screen to be tested is determined according to the target brightness value;

[0099] If the target brightness value does not meet the preset detection condition, the process returns to the step of selecting the target exposure duration from different preset exposure durations.

[0100] Among them, whether the target brightness value meets the preset detection conditions can be determined based on the number of pixels of the screen to be tested. For example, when the difference between the number of pixels of the screen to be tested and the number of target brightness values ​​is within a preset range, it can be determined that the target brightness value meets the preset detection conditions.

[0101] In an embodiment of the present application, a target exposure time is screened out from different preset exposure times, and a target image is obtained under the target exposure time. If the target brightness value determined based on the target grayscale value of the target image meets the preset detection condition, the display parameter detection result of the screen to be tested is determined based on the target brightness value. If the target brightness value determined based on the target grayscale value of the target image does not meet the preset detection condition, the process returns to the step of screening out the target exposure time from different preset exposure times, thereby eliminating the need to obtain all target images with different preset exposure times, reducing the time for obtaining the target image, speeding up the speed of obtaining the target brightness value, and thereby speeding up the speed of obtaining the display parameter detection result of the screen to be tested.

[0102] Optionally, in order to further speed up the speed of obtaining the target brightness value, when the terminal screens out the target exposure time from different preset exposure times and obtains the target image under the target exposure time, after determining the target grayscale value of the target image, the target grayscale value can be added to and subtracted from the first grayscale value to obtain multiple calculated grayscale values, and then the target grayscale value, the calculated grayscale value, and the grayscale value between the target grayscale value and the calculated grayscale value are substituted into the brightness grayscale mapping strategy for mapping to obtain multiple target brightness values, and then it is determined whether the target brightness value meets the preset detection conditions.

[0103] The first grayscale value is a preset grayscale value, which can be selected according to actual conditions and is not limited in the embodiment of the present application.

[0104] When the display parameter includes brightness, the process of determining the display parameter detection result of the screen to be tested according to the target brightness value may be: determining the brightness detection result of the screen to be tested according to the target brightness.

[0105] When the display parameters include chromaticity, the process of determining the display parameter detection result of the screen to be tested according to the target brightness value can be:

[0106] Acquire a first image of the screen under test at different preset exposure times through a second filter corresponding to the second stimulation parameter, and acquire a second image of the screen under test at different preset exposure times through a third filter corresponding to the third stimulation parameter;

[0107] determining a second stimulation value of a second stimulation parameter according to the first image and the brightness-grayscale mapping strategy;

[0108] determining a third stimulation value of a third stimulation parameter according to the second image and the brightness-grayscale mapping strategy;

[0109] The chromaticity detection result of the screen to be tested is determined according to the first stimulus value, the second stimulus value and the third stimulus value.

[0110] At this time, the target image can be an image captured under the first filter, and the transmission spectrum of the first filter can be T1(λ). T1(λ) can be determined according to the spectral luminous efficiency function and the image sensor quantum efficiency function. That is, the transmission spectrum of the first filter can be:

[0111]

[0112] λ represents wavelength, V(λ) represents spectral luminous efficiency function, and Q(λ) represents image sensor quantum efficiency function.

[0113] The transmission spectrum of the second filter can be T2(λ), which can be determined according to the x color matching function and the spectral sensitivity of the image sensor to the incident light. That is, the transmission spectrum of the second filter can be:

[0114]

[0115] represents the x color matching function, Q(λ) represents the quantum efficiency function of the image sensor, and can also represent the spectral sensitivity of the image sensor in response to incident light.

[0116] The transmission spectrum of the third filter may be T3(λ), which may be determined based on the z color matching function and the spectral sensitivity of the image sensor to the incident light. That is, the transmission spectrum of the third filter may be:

[0117]

[0118] represents the z color matching function, Q(λ) represents the quantum efficiency function of the image sensor, and can also represent the spectral sensitivity of the image sensor in response to incident light.

[0119] The target brightness value may be a first stimulus value of the first stimulus parameter. The first stimulus parameter, the second stimulus parameter, and the third stimulus parameter may be referred to as three stimulus parameters. The first stimulus parameter may be a Y stimulus parameter, the second stimulus parameter may be an X stimulus parameter, and the third stimulus parameter may be a Z stimulus parameter. Alternatively, the first stimulus parameter may be a green primary color stimulus parameter, the second stimulus parameter may be a red primary color stimulus parameter, and the third stimulus parameter may be a blue primary color stimulus parameter.

[0120] The terminal can determine a first target grayscale value based on the first image, and then substitute the first target grayscale value into the brightness grayscale mapping strategy for mapping processing to obtain a second stimulation value of the second stimulation parameter; determine a second target grayscale value based on the second image, and then substitute the second target grayscale value into the brightness grayscale mapping strategy for mapping processing to obtain a third stimulation value of the third stimulation parameter.

[0121] In an embodiment of the present application, the first stimulus value, the second stimulus value, and the third stimulus value are determined by using images captured under different filters and a brightness grayscale mapping strategy, and then the chromaticity detection result of the screen to be tested is determined based on the first stimulus value, the second stimulus value, and the third stimulus value.

[0122] The first stimulus value, the second stimulus value, and the third stimulus value may be normalized to obtain the chromaticity coordinates of the screen to be tested, and the chromaticity detection result of the screen to be tested may be determined based on the chromaticity coordinates. The normalization process may be:

[0123]

[0124]

[0125] x and y represent the chromaticity coordinates of the screen to be tested.

[0126] In some embodiments, determining a second stimulation value of a second stimulation parameter according to the first image and the brightness-to-grayscale mapping strategy includes:

[0127] determining a candidate stimulus value of a second stimulus parameter according to the first image and the brightness-grayscale mapping strategy;

[0128] obtaining a calibration coefficient of a second stimulation parameter;

[0129] The candidate stimulation value of the second stimulation parameter is calibrated according to the calibration coefficient of the second stimulation parameter to obtain the second stimulation value of the second stimulation parameter.

[0130] The terminal may determine a first target grayscale value based on the first image, and then substitute the first target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain a candidate stimulation value of the second stimulation parameter.

[0131] In the embodiment of the present application, the calibration coefficient of the second stimulation parameter is multiplied by the candidate stimulation value of the second stimulation parameter to obtain the second stimulation value of the second stimulation parameter, thereby calibrating the second stimulation value and making the obtained second stimulation value more accurate.

[0132] In some other embodiments, before obtaining the calibration coefficient of the second stimulation parameter, the method further includes:

[0133] Acquire a first calibration image captured under a first optical filter, and determine a grayscale value of the first calibration image;

[0134] Acquire a second calibration image captured under a second optical filter, and determine a grayscale value of the second calibration image;

[0135] A calibration coefficient of the second stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the second calibration image.

[0136] The first calibration image and the second calibration image may be images of a calibration screen, the grayscale value of the first calibration image may refer to the grayscale value of a central pixel point of the first calibration image, and the grayscale value of the second calibration image may refer to the grayscale value of a central pixel point of the second calibration image, or the grayscale value of the first calibration image may refer to the grayscale value of a central pixel point of the calibration screen, and the grayscale value of the second calibration image may refer to the grayscale value of a central pixel point of the calibration screen.

[0137] The process of determining the calibration coefficient of the second stimulation parameter based on the grayscale value of the first calibration image and the grayscale value of the second calibration image can be: dividing the grayscale value of the first calibration image by the grayscale value of the second calibration image to obtain a ratio, and using the ratio as the calibration coefficient of the second stimulation parameter. That is, the grayscale value of the first calibration image and the grayscale value of the second calibration image can be substituted into the following formula to obtain the calibration coefficient of the second stimulation parameter:

[0138]

[0139] K X represents the calibration coefficient of the second stimulus parameter, g Y Represents the grayscale value of the first calibration image, g X Represents the grayscale value of the second calibration image.

[0140] In an embodiment of the present application, since the isoenergetic white point coordinates determine the brightness mixing ratio of the three channels, the calibration screen can display the isoenergetic white point coordinates (the isoenergetic calibration point coordinates are (0.333, 0.333)), and then the first calibration image of the calibration screen is collected under the first filter, and the second calibration image of the calibration screen is collected under the second filter, so as to determine the calibration coefficient of the second stimulation parameter based on the grayscale value of the first calibration image and the grayscale value of the second calibration image.

[0141] In some other embodiments, determining a third stimulation value of a third stimulation parameter according to the second image and the brightness-to-grayscale mapping strategy includes:

[0142] determining a candidate stimulus value of a third stimulus parameter according to the second image and the brightness-grayscale mapping strategy;

[0143] obtaining a calibration coefficient of a third stimulation parameter;

[0144] The candidate stimulation value of the third stimulation parameter is calibrated according to the calibration coefficient of the third stimulation parameter to obtain a third stimulation value of the third stimulation parameter.

[0145] The terminal may determine a second target grayscale value based on the second image, and then substitute the second target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain a candidate stimulation value of the third stimulation parameter.

[0146] In the embodiment of the present application, the calibration coefficient of the third stimulation parameter is multiplied by the candidate stimulation value of the third stimulation parameter to obtain the third stimulation value of the third stimulation parameter, thereby calibrating the third stimulation value and making the obtained third stimulation value more accurate.

[0147] Optionally, before obtaining the calibration coefficient of the third stimulation parameter, the method further includes:

[0148] Acquire a first calibration image captured under a first optical filter, and determine a grayscale value of the first calibration image;

[0149] Acquire a third calibration image captured under a third optical filter, and determine a grayscale value of the third calibration image;

[0150] A calibration coefficient of the third stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the third calibration image.

[0151] The first calibration image and the third calibration image may be images of a calibration screen, the grayscale value of the first calibration image may refer to the grayscale value of a central pixel of the first calibration image, and the grayscale value of the third calibration image may refer to the grayscale value of a central pixel of the third calibration image, or the grayscale value of the first calibration image may refer to the grayscale value of a central pixel of the calibration screen, and the grayscale value of the third calibration image may refer to the grayscale value of a central pixel of the calibration screen.

[0152] The process of determining the calibration coefficient of the third stimulation parameter based on the grayscale values ​​of the first calibration image and the grayscale values ​​of the third calibration image can be: dividing the grayscale value of the first calibration image by the grayscale value of the third calibration image to obtain a ratio, and using the ratio as the calibration coefficient of the third stimulation parameter. That is, the grayscale value of the first calibration image and the grayscale value of the third calibration image can be substituted into the following formula to obtain the calibration coefficient of the third stimulation parameter:

[0153] K Z represents the calibration coefficient of the third stimulus parameter, g Y Represents the grayscale value of the first calibration image, g Z Represents the grayscale value of the third calibration image.

[0154] For example, Figure 2As shown, the image sensor is an area array sensor, the calibration screen is a white field meter, the preset exposure time is t, the white field meter displays the coordinates of the isoenergetic white point, and the white field meter is photographed through the imaging lens, the first filter, and the area array sensor at the exposure time t to obtain a first calibration image, and the grayscale value of the first calibration image is determined.

[0155] The white field meter is photographed through the imaging lens, the second filter, and the area array sensor at an exposure time t to obtain a second calibration image, and the grayscale value of the second calibration image is determined.

[0156] A calibration coefficient of the second stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the second calibration image.

[0157] The white field meter is photographed through the imaging lens, the third filter, and the area array sensor at an exposure time t to obtain a third calibration image, and the grayscale value of the third calibration image is determined.

[0158] A calibration coefficient of the third stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the third calibration image.

[0159] In some other embodiments, before obtaining different preset exposure durations, the method further includes:

[0160] Get multiple calibrated brightness values ​​and different preset exposure times;

[0161] Acquire calibration images of the calibration screen for multiple calibration brightness values ​​at each preset exposure time;

[0162] Determining, according to the calibration image, calibration grayscale values ​​corresponding to the plurality of calibration brightness values;

[0163] According to the multiple calibrated brightness values ​​and calibrated grayscale values, a brightness-to-grayscale mapping strategy corresponding to the preset exposure time is determined.

[0164] When the brightness-to-grayscale mapping strategy is represented by a mapping function, the process of obtaining multiple calibrated brightness values ​​can be:

[0165] Get the intermediate calibrated brightness value;

[0166] The middle calibrated brightness value is adjusted by multiples to obtain the multiple calibrated brightness value;

[0167] The intermediate calibrated brightness value and the multiple calibrated brightness value are used as multiple calibrated brightness values.

[0168] The multiple calibrated brightness value refers to a multiple of the intermediate calibrated brightness value. For example, the multiple calibrated brightness value may refer to half of the intermediate calibrated brightness value, or the multiple calibrated brightness value may refer to twice the intermediate calibrated brightness value.

[0169] It should be understood that the terminal can filter out a calibrated exposure time from different preset exposure times, and then obtain a calibrated image of the calibrated screen for multiple calibrated brightness values ​​under the calibrated exposure time, and determine the calibrated grayscale values ​​corresponding to the multiple calibrated brightness values ​​according to the calibrated image. When determining the brightness-grayscale mapping strategy corresponding to the calibrated exposure time based on the multiple calibrated brightness values ​​and the calibrated grayscale values, it can be determined whether the brightness-grayscale mapping strategy covers the local maximum brightness of the calibrated screen. If the brightness-grayscale mapping strategy does not cover the local maximum brightness of the calibrated screen, return to the step of filtering out the calibrated exposure time from different preset exposure times.

[0170] Alternatively, the terminal may first use the initial exposure time as the preset exposure time. In this case, there is only one preset exposure time, and the preset exposure time is directly used as the calibrated exposure time. Then, when the brightness grayscale mapping strategy does not cover the local maximum brightness of the calibrated screen, the initial exposure time is adjusted to obtain the adjusted exposure time. The adjusted exposure time is used as the calibrated exposure time, and the process returns to obtain the calibrated image of the calibrated screen for multiple calibrated brightness values ​​under the calibrated exposure time. At this time, the preset exposure time includes the adjusted exposure time and the initial exposure time.

[0171] Optionally, since the brightness grayscale mapping curve includes a nonlinear part and a linear part, in order to more accurately obtain the brightness grayscale mapping curve, the calibrated brightness value includes an intermediate calibrated brightness value, and the initial exposure time is obtained, including:

[0172] Obtaining initial calibration images of the calibration screen for intermediate calibration brightness values ​​at different exposure times;

[0173] Determine the initial grayscale value corresponding to the initial calibration image;

[0174] The exposure time of the initial calibration image corresponding to the initial grayscale value that meets the preset grayscale value is used as the initial exposure time.

[0175] The preset grayscale value can be a function value on the linear part. For example, the mapping curve of brightness grayscale can be as follows: Figure 3 As shown, the horizontal axis (Relative Intensity) represents the exposure amount, and the vertical axis (Gray Scale) represents the grayscale. At this time, the preset grayscale value can be a 50% grayscale value or a 49% grayscale value.

[0176] In an embodiment of the present application, the initial grayscale value of the function value on the linear part and the exposure time of the corresponding initial calibration image are used as the initial exposure time, and then the initial exposure time is adjusted to obtain different preset exposure times, so that the brightness-grayscale mapping strategy of different preset exposure times is a linear mapping strategy.

[0177] For example, when the brightness grayscale mapping strategy is expressed by a mapping function, it can be expressed as follows: Figure 4 The calibration screen is a white field meter, which displays n nits of 6500K white light, i.e., the calibration brightness value is n. The exposure time is adjusted so that the grayscale value of the central pixel of the initial calibration image acquired through the imaging lens, the first filter, and the area array sensor is 50%. The exposure time at this time is recorded as the initial exposure time t.

[0178] The white field meter displays n / 2 nits of 6500K white light, that is, the calibrated brightness value is n / 2. Under the initial exposure time, the initial calibration image is collected through the imaging lens, the first filter and the area array sensor. The calibrated grayscale value of the initial calibration image is g1.

[0179] The white field meter displays 2n nits of 6500K white light, that is, the calibrated brightness value is 2n. Under the initial exposure time, the initial calibration image is collected through the imaging lens, the first filter and the area array sensor. The calibrated grayscale value of the initial calibration image is g2.

[0180] According to n, n / 2, 2n, 50% gray value, g1 and g2, the brightness gray mapping sub-function is obtained by fitting g represents grayscale, f t represents brightness, and k1, k2, and w are linear fitting parameters. At this point, if the brightness-to-grayscale mapping strategy does not cover the local maximum brightness of the calibration screen, adjust the initial exposure time to half the initial exposure time, and the white field meter displays n1 nits of white light. Return to the step of adjusting the exposure time so that the grayscale value of the central pixel of the initial calibration image acquired through the imaging lens, the first filter, and the area array sensor is 50% grayscale.

[0181] If the brightness-grayscale mapping strategy covers the local maximum brightness of the calibration screen, the brightness-grayscale mapping sub-function is used as the brightness-grayscale mapping function f of the image sensor.

[0182] At this time, the brightness grayscale mapping function f can be as follows Figure 5 As shown in the gray area, the horizontal axis (RelativeIntensity) represents the exposure, and the vertical axis (Gray Scale) represents the grayscale. That is, the brightness grayscale mapping function f is a piecewise linear function, including the brightness grayscale mapping sub-function f t , brightness grayscale mapping subfunction f t / 2 , brightness grayscale mapping subfunction f t / 4 , brightness grayscale mapping subfunction f t / 8 , brightness grayscale mapping subfunction f t / 16 And the brightness grayscale mapping subfunction f t / 32 .

[0183] From the above, it can be seen that in an embodiment of the present application, a target image of the screen to be tested under different preset exposure times is obtained; the target grayscale value of the target image is determined, and a brightness-grayscale mapping strategy corresponding to different preset exposure times is obtained; the target grayscale value is substituted into the brightness-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value; based on the target brightness value, the display parameter detection result of the screen to be tested is determined, and the target grayscale values ​​of the target images under different preset exposure times are mapped through the brightness-grayscale mapping strategy with different preset exposure times, so that a plurality of target brightness values ​​can be obtained, so that the display parameter detection result of the screen to be tested can be determined based on the plurality of target brightness values, thereby improving the accuracy of the display parameter detection result.

[0184] The following is based on Figure 6 , taking the image sensor as the area array sensor, the brightness grayscale mapping strategy as the brightness grayscale mapping function, the display parameters include brightness and color temperature, that is, the display parameter detection results include brightness detection results and color temperature detection results, and the process of determining the display parameter detection results is explained.

[0185] The screen to be tested is placed at the imaging center of the camera. The camera's position is adjusted so that the image field covers the screen to be tested, and the imaging lens is adjusted to focus. Using the imaging lens, the first filter, and the area array sensor, a target image of the screen to be tested is captured at a target exposure time (in this case, the target exposure time is t). Based on the target image, a target grayscale value for the pixel on the screen to be tested is determined. The target grayscale value is added to and subtracted from the first grayscale value to obtain a calculated grayscale value. The grayscale value between the target grayscale value and the calculated grayscale value, as well as the target grayscale value and the calculated grayscale value, are substituted into the brightness-to-grayscale mapping function corresponding to the target exposure time to obtain the target brightness value for the pixel on the screen to be tested.

[0186] Determine whether the target brightness value meets the preset detection conditions. If not, adjust the target exposure time by a multiple to obtain the adjusted exposure time. Use the adjusted exposure time as the target exposure time, and return to execute. Capture the target image of the screen to be tested at the target exposure time through the imaging lens, the first filter, and the area array sensor.

[0187] If the preset detection conditions are met, the first filter is replaced with the second filter, and the first image of the screen to be tested is collected through the imaging lens, the second filter and the area array sensor at the target exposure time (at this time, the target exposure time is t), and the first target grayscale value of the pixel point on the screen to be tested is determined according to the first image, and the first grayscale value is added to and subtracted from the first target grayscale value to obtain a first calculated grayscale value, and the grayscale value between the first target grayscale value and the first calculated grayscale value, the first target grayscale value and the first calculated grayscale value are substituted into the brightness grayscale mapping function corresponding to the target exposure time to obtain a candidate stimulation value of the second stimulation parameter of the pixel point on the screen to be tested, and the candidate stimulation value of the second stimulation parameter is calibrated according to the calibration coefficient of the second stimulation parameter to obtain the second stimulation value of the second stimulation parameter.

[0188] Determine whether the second stimulus value satisfies a first preset detection condition (the first preset detection condition can be determined based on the number of pixels of the screen to be tested. For example, when the difference between the number of pixels of the screen to be tested and the number of the second stimulus value is within a first preset range, it can be determined that the second stimulus value satisfies the first preset detection condition). If the first preset detection condition is not satisfied, adjust the target exposure duration by a multiple to obtain an adjusted exposure duration, use the adjusted exposure duration as the target exposure duration, and return to execute, using the imaging lens, the second filter, and the area array sensor, to capture a first image of the screen to be tested at the target exposure duration.

[0189] If the first preset detection condition is met, the second filter is replaced with the third filter, and a second image of the screen to be tested is collected through the imaging lens, the third filter and the area array sensor at the target exposure time (at this time, the target exposure time is t). According to the second image, the second target grayscale value of the pixel point on the screen to be tested is determined, and the first grayscale value is added to and subtracted from the second target grayscale value to obtain a second calculated grayscale value. The grayscale value between the second target grayscale value and the second calculated grayscale value, the second target grayscale value and the second calculated grayscale value are substituted into the brightness grayscale mapping function corresponding to the target exposure time to obtain a candidate stimulation value of the third stimulation parameter of the pixel point on the screen to be tested. According to the calibration coefficient of the third stimulation parameter, the candidate stimulation value of the third stimulation parameter is calibrated to obtain the third stimulation value of the third stimulation parameter.

[0190] Determine whether the third stimulus value satisfies a second preset detection condition (the second preset detection condition can be determined based on the number of pixels of the screen to be tested. For example, when the difference between the number of pixels of the screen to be tested and the number of the third stimulus value is within a second preset range, it can be determined that the third stimulus value satisfies the second preset detection condition). If the second preset detection condition is not satisfied, adjust the target exposure duration by a multiple to obtain an adjusted exposure duration, use the adjusted exposure duration as the target exposure duration, and return to execute, using the imaging lens, the third filter, and the area array sensor to capture a second image of the screen to be tested at the target exposure duration.

[0191] If the second preset detection condition is met, the target brightness value is output and used as the first stimulus value, and normalization processing is performed according to the first stimulus value, the second stimulus value and the third stimulus value to obtain the chromaticity coordinates of the screen to be tested.

[0192] To facilitate better implementation of the parameter detection method provided in the embodiment of the present application, the embodiment of the present application also provides a device based on the above parameter detection method. The meanings of the terms are the same as those in the above parameter detection method, and the specific implementation details can be referred to the description in the method embodiment.

[0193] For example, Figure 7 As shown, the parameter detection device may include:

[0194] The image acquisition module 701 is used to acquire target images of the screen to be tested under different preset exposure times.

[0195] The first determining module 702 is configured to determine a target grayscale value of a target image and obtain brightness-to-grayscale mapping strategies corresponding to different preset exposure times.

[0196] The grayscale mapping module 703 is used to substitute the target grayscale value into the brightness-to-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value.

[0197] The second determining module 704 is configured to determine a display parameter detection result of the screen to be tested according to the target brightness value.

[0198] Optionally, the image acquisition module 701 is specifically configured to perform:

[0199] Select the target exposure duration from different preset exposure durations;

[0200] Acquire the target image at the target exposure time.

[0201] Accordingly, the second determining module 704 is specifically configured to execute:

[0202] If the target brightness value meets the preset detection conditions, the display parameter detection result of the screen to be tested is determined according to the target brightness value;

[0203] If the target brightness value does not meet the preset detection condition, the process returns to the step of selecting the target exposure duration from different preset exposure durations.

[0204] Optionally, the first determining module 702 is specifically configured to execute:

[0205] Get the transformation matrix between the screen to be tested and the camera that obtains the target image;

[0206] Perform transformation processing on the target image according to the transformation matrix to obtain a transformed image;

[0207] According to the transformed image, the target grayscale value of the target image is determined.

[0208] Optionally, the first determining module 702 is specifically configured to execute:

[0209] Determine the coordinates of multiple source points of the screen to be tested according to the target image;

[0210] According to the number of pixels of the screen to be tested, determine the coordinates of multiple target points corresponding to the camera;

[0211] According to the source point coordinates and the target point coordinates, the transformation matrix between the screen to be tested and the camera is determined.

[0212] Optionally, the display parameter detection result includes a chromaticity detection result, the target brightness value is a first stimulation value of the first stimulation parameter, and the target image is an image captured under a first filter.

[0213] Accordingly, the second determining module 704 is specifically configured to execute:

[0214] Acquire a first image of the screen under test at different preset exposure times through a second filter corresponding to the second stimulation parameter, and acquire a second image of the screen under test at different preset exposure times through a third filter corresponding to the third stimulation parameter;

[0215] determining a second stimulation value of a second stimulation parameter according to the first image and the brightness-grayscale mapping strategy;

[0216] determining a third stimulation value of a third stimulation parameter according to the second image and the brightness-grayscale mapping strategy;

[0217] The chromaticity detection result of the screen to be tested is determined according to the first stimulus value, the second stimulus value and the third stimulus value.

[0218] Optionally, the second determining module 704 is specifically configured to execute:

[0219] determining a candidate stimulus value of a second stimulus parameter according to the first image and the brightness-grayscale mapping strategy;

[0220] obtaining a calibration coefficient of a second stimulation parameter;

[0221] The candidate stimulation value of the second stimulation parameter is calibrated according to the calibration coefficient of the second stimulation parameter to obtain the second stimulation value of the second stimulation parameter.

[0222] Optionally, the parameter detection device further includes:

[0223] Calibration module, used to perform:

[0224] Acquire a first calibration image captured under a first optical filter, and determine a grayscale value of the first calibration image;

[0225] Acquire a second calibration image captured under a second optical filter, and determine a grayscale value of the second calibration image;

[0226] A calibration coefficient of the second stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the second calibration image.

[0227] Optionally, the calibration module is further configured to perform:

[0228] Get multiple calibrated brightness values ​​and different preset exposure times;

[0229] Acquire calibration images of the calibration screen for multiple calibration brightness values ​​at each preset exposure time;

[0230] Determining, according to the calibration image, calibration grayscale values ​​corresponding to the plurality of calibration brightness values;

[0231] According to the multiple calibrated brightness values ​​and calibrated grayscale values, a brightness-to-grayscale mapping strategy corresponding to the preset exposure time is determined.

[0232] Optionally, the calibration module is specifically configured to perform:

[0233] Get the initial exposure duration;

[0234] Adjusting the initial exposure time to obtain an adjusted exposure time;

[0235] Different preset exposure times are determined according to the initial exposure time and the adjusted exposure time.

[0236] Optionally, the calibrated brightness value includes an intermediate calibrated brightness value. Accordingly, the calibration module is specifically configured to execute:

[0237] Obtaining initial calibration images of the calibration screen for intermediate calibration brightness values ​​at different exposure times;

[0238] Determine the initial grayscale value corresponding to the initial calibration image;

[0239] The exposure time of the initial calibration image corresponding to the initial grayscale value that meets the preset grayscale value is used as the initial exposure time.

[0240] During specific implementation, the above modules can be implemented as independent entities, or they can be arbitrarily combined and implemented as the same or several entities. The specific implementation methods and corresponding beneficial effects of the above modules can be found in the previous method embodiments and will not be repeated here.

[0241] The embodiment of the present application also provides an electronic device, which may be a server or a terminal, etc. Figure 8 , which shows a schematic structural diagram of an electronic device involved in an embodiment of the present application, specifically:

[0242] The electronic device may include one or more processors 801, one or more computer-readable storage media memories 802, a power supply 803, an input unit 804, and other components. It will be understood by those skilled in the art that Figure 8 The electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0243] The processor 801 is the control center of the electronic device. It connects all parts of the electronic device using various interfaces and circuits. It performs various functions of the electronic device and processes data by running or executing computer programs and / or modules stored in the memory 802 and accessing data stored in the memory 802. Optionally, the processor 801 may include one or more processing cores. Preferably, the processor 801 may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into the processor 801.

[0244] The memory 802 can be used to store computer programs and modules. The processor 801 executes various functional applications and data processing by running the computer programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a computer program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 802 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0245] The electronic device also includes a power supply 803 for supplying power to various components. Preferably, the power supply 803 can be logically connected to the processor 801 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 803 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0246] The electronic device may further include an input unit 804, which may be configured to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0247] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 801 in the electronic device will load the executable files corresponding to one or more computer program processes into the memory 802 according to the following instructions, and the processor 801 will run the computer program stored in the memory 802 to implement various functions, such as:

[0248] Obtain target images of the screen to be tested under different preset exposure times;

[0249] Determine the target grayscale value of the target image and obtain the brightness-to-grayscale mapping strategy corresponding to different preset exposure times;

[0250] Substitute the target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain the target brightness value corresponding to the target grayscale value;

[0251] According to the target brightness value, the display parameter detection result of the screen to be tested is determined.

[0252] Optionally, the electronic device may further include an imaging lens and an image sensor. In this case, the electronic device may be as shown in FIG9 . Figure 9 1 represents the screen to be tested, 2 represents the imaging lens, 3 represents the filter (which can be the first filter, the second filter, or the third filter), 4 represents the image sensor, 5 represents the processor, and 6 represents the transmission line. This simple structure can be used to achieve a display parameter detection structure, with low requirements for the image sensor and reduced costs.

[0253] The imaging lens and image sensor are used to capture a target image. The imaging lens's corresponding object plane field of view is equal to or greater than a first multiple of the diagonal length of the screen to be measured. This allows the imaging lens to capture outgoing light parallel to the screen to be measured, preventing the viewing angle of the screen to be measured from affecting the display parameter detection results, and improving the accuracy of the display parameter detection results. Optionally, the imaging lens's diagonal viewing angle is less than or equal to the first angle.

[0254] For example, the first multiple may be 1.2 times, and the first angle may be 12°.

[0255] Optionally, the number of pixels of the image sensor is greater than the second multiple of the number of pixels of the screen to be tested, and the row pixels of the image sensor are parallel to the row pixels of the screen to be tested, and the column pixels of the image sensor are parallel to the column pixels of the screen to be tested, thereby avoiding the imaging moiré problem and further improving the accuracy of the display parameter detection results.

[0256] For example, the second multiple can be set to 4 times.

[0257] Optionally, the image sensor may be an area array sensor that uses a global shutter and has no infrared cutoff filter.

[0258] Optionally, the imaging lens, filter and image sensor can be set on a one-dimensional mobile platform, and a guide rail is provided under the mobile platform for adjusting the position of the imaging surface. The position of the mobile platform can be locked, and the screen to be tested can be placed on a light-absorbing dark background plane.

[0259] The specific implementation methods and corresponding beneficial effects of the above operations can be found in the detailed description of the parameter detection method above, which will not be elaborated here.

[0260] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by a computer program, or by controlling related hardware through a computer program. The computer program may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0261] To this end, an embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor to execute the steps of any parameter detection method provided in the embodiment of the present application. For example, the computer program can execute the following steps:

[0262] Obtain target images of the screen to be tested under different preset exposure times;

[0263] Determine the target grayscale value of the target image and obtain the brightness-to-grayscale mapping strategy corresponding to different preset exposure times;

[0264] Substitute the target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain the target brightness value corresponding to the target grayscale value;

[0265] According to the target brightness value, the display parameter detection result of the screen to be tested is determined.

[0266] The specific implementation methods and corresponding beneficial effects of the above operations can be found in the previous embodiments and will not be described in detail here.

[0267] The computer-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0268] Since the computer program stored in the computer-readable storage medium can execute the steps in any parameter detection method provided in the embodiments of the present application, the beneficial effects that can be achieved by any parameter detection method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0269] According to one aspect of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the above-described parameter detection method.

[0270] The above is a detailed introduction to a parameter detection method, device, electronic device and computer storage medium provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A parameter detection method, characterized in that: include: Obtain target images of the screen to be tested under different preset exposure times; Determining a target grayscale value of the target image, and obtaining brightness-to-grayscale mapping strategies corresponding to the different preset exposure times; Substituting the target grayscale value into the brightness-to-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value; Determining a display parameter detection result of the screen to be tested according to the target brightness value; The display parameter detection result includes a chromaticity detection result, the target brightness value is a first stimulation value of a first stimulation parameter, and the target image is an image captured under a first filter; Determining the display parameter detection result of the screen to be tested according to the target brightness value includes: Acquire a first image of the screen under test at the different preset exposure times through a second filter corresponding to the second stimulation parameter, and acquire a second image of the screen under test at the different preset exposure times through a third filter corresponding to the third stimulation parameter; determining a second stimulation value of the second stimulation parameter according to the first image and the brightness-grayscale mapping strategy; determining a third stimulation value of the third stimulation parameter according to the second image and the brightness-grayscale mapping strategy; A chromaticity detection result of the screen to be tested is determined according to the first stimulus value, the second stimulus value, and the third stimulus value.

2. The parameter detection method according to claim 1, characterized in that: The step of obtaining target images of the screen to be tested under different preset exposure times includes: Select the target exposure duration from different preset exposure durations; Acquire a target image at the target exposure time; Determining the brightness detection result of the screen to be tested according to the target brightness value includes: If the target brightness value satisfies a preset detection condition, determining a display parameter detection result of the screen to be tested according to the target brightness value; If the target brightness value does not meet the preset detection condition, the process returns to the step of selecting the target exposure duration from different preset exposure durations.

3. The parameter detection method according to claim 1, characterized in that: Determining the target grayscale value of the target image includes: Obtaining a transformation matrix between the screen to be tested and the camera that obtains the target image; Performing transformation processing on the target image according to the transformation matrix to obtain a transformed image; A target grayscale value of the target image is determined according to the transformed image.

4. The parameter detection method according to claim 3, characterized in that: The obtaining of the transformation matrix between the screen to be tested and the camera includes: Determining the coordinates of multiple source points of the screen to be measured according to the target image; Determining the coordinates of multiple target points corresponding to the camera according to the number of pixels of the screen to be tested; A transformation matrix between the screen to be measured and the camera is determined according to the source point coordinates and the target point coordinates.

5. The parameter detection method according to claim 1, characterized in that: Determining a second stimulation value of the second stimulation parameter according to the first image and the brightness-grayscale mapping strategy includes: determining candidate stimulation values ​​of the second stimulation parameter according to the first image and the brightness-grayscale mapping strategy; obtaining a calibration coefficient of the second stimulation parameter; The candidate stimulation value of the second stimulation parameter is calibrated according to the calibration coefficient of the second stimulation parameter to obtain the second stimulation value of the second stimulation parameter.

6. The parameter detection method according to claim 5, characterized in that: Before obtaining the calibration coefficient of the second stimulation parameter, the method further includes: Acquire a first calibration image captured under the first optical filter, and determine a grayscale value of the first calibration image; Acquire a second calibration image captured under the second optical filter, and determine a grayscale value of the second calibration image; A calibration coefficient of the second stimulation parameter is determined according to the grayscale value of the first calibration image and the grayscale value of the second calibration image.

7. The parameter detection method according to any one of claims 1 to 6, characterized in that: Before obtaining different preset exposure durations, the method further includes: Get multiple calibrated brightness values ​​and different preset exposure times; Acquire a calibration image of the calibration screen for the multiple calibration brightness values ​​at each of the preset exposure times; Determining, based on the calibration image, calibration grayscale values ​​corresponding to the plurality of calibration brightness values; A brightness-to-grayscale mapping strategy corresponding to the preset exposure duration is determined according to the multiple calibrated brightness values ​​and the calibrated grayscale values.

8. The parameter detection method according to claim 7, characterized in that: The obtaining of different preset exposure durations includes: Get the initial exposure duration; Adjusting the initial exposure time to obtain an adjusted exposure time; The different preset exposure durations are determined according to the initial exposure duration and the adjusted exposure duration.

9. The parameter detection method according to claim 8, characterized in that: The calibrated brightness value includes an intermediate calibrated brightness value, and obtaining the initial exposure duration includes: Acquiring an initial calibration image of the calibration screen for the intermediate calibration brightness value under different exposure times; Determining an initial grayscale value corresponding to the initial calibration image; The exposure time of the initial calibration image corresponding to the initial grayscale value that meets the preset grayscale value is used as the initial exposure time.

10. A parameter detection device, characterized in that: include: An image acquisition module is used to acquire target images of the screen to be tested under different preset exposure times; A first determining module is configured to determine a target grayscale value of the target image and obtain brightness-to-grayscale mapping strategies corresponding to the different preset exposure times; A grayscale mapping module is used to substitute the target grayscale value into the brightness-grayscale mapping strategy for mapping processing to obtain a target brightness value corresponding to the target grayscale value; A second determining module is used to determine the display parameter detection result of the screen to be tested according to the target brightness value; The display parameter detection result includes a chromaticity detection result, the target brightness value is a first stimulation value of a first stimulation parameter, and the target image is an image captured under a first filter; Determining the display parameter detection result of the screen to be tested according to the target brightness value includes: Acquire a first image of the screen under test at the different preset exposure times through a second filter corresponding to the second stimulation parameter, and acquire a second image of the screen under test at the different preset exposure times through a third filter corresponding to the third stimulation parameter; determining a second stimulation value of the second stimulation parameter according to the first image and the brightness-grayscale mapping strategy; determining a third stimulation value of the third stimulation parameter according to the second image and the brightness-grayscale mapping strategy; A chromaticity detection result of the screen to be tested is determined according to the first stimulus value, the second stimulus value, and the third stimulus value.

11. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the parameter detection method according to any one of claims 1 to 9.

12. The electronic device according to claim 11, wherein: The electronic device also includes an imaging lens and an image sensor, which are used to capture the target image. The object plane field of view corresponding to the imaging lens is equal to or greater than a first multiple of the diagonal length of the screen to be measured.

13. The electronic device according to claim 12, wherein: The number of pixels of the image sensor is greater than the second multiple of the number of pixels of the screen to be tested, and the row pixels of the image sensor are parallel to the row pixels of the screen to be tested, and the column pixels of the image sensor are parallel to the column pixels of the screen to be tested.

14. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the parameter detection method according to any one of claims 1 to 9.

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