Test positioning method and device, storage medium and method for providing target image

Abstract

The invention provides a test positioning method for a display, comprising the following steps: displaying a target image on the display, the target image comprising a plurality of first positioning points and a plurality of second positioning points, the second positioning points being different from the first positioning points in shape and / or size, and the first positioning points being different from the second positioning points in shape and / or size; wherein the second positioning point is located at a preset position of the target image; shooting the displayed target image to obtain a first shot image; identifying a second positioning point in the first shot image; determining a homography transformation matrix between the target image and the shot image according to the preset position of the second positioning point in the target image and the actual position of the second positioning point in the first shot image; and identifying a first positioning point in the first shot image, and converting the first positioning point and the second positioning point through the homography transformation matrix to obtain a mapping point set between the target image and the first shot image. The invention also provides a test positioning device for the display. According to the invention, the test positioning precision of the display can be remarkably improved, so that the user experience of the display is improved.

Description

Technical Field

[0001] The present invention generally relates to the field of display technologies, and more specifically, to a test positioning method, apparatus, storage medium, and method for providing a target image. Background Art

[0002] At present, with the booming development of display technologies, the waveguide module, as a core component of near-eye displays such as augmented reality (AR) and virtual reality (VR), has become increasingly important. As the "visual center" of the device, the waveguide module shoulders the crucial task of efficiently guiding image light into the user's field of view, and largely dominates the display experience of AR / VR devices.

[0003] However, the currently widely used diffractive waveguide module has an obvious shortcoming. Within the Eyebox (i.e., the human eye visible area), its brightness and chromaticity uniformity are poor. The emergence of this problem seriously disrupts the immersive visual experience brought by AR / VR devices to users, and urgently needs to be solved.

[0004] Currently, the problem of brightness and chromaticity uniformity of displays is generally solved through the test positioning technology of displays. The test positioning of a display refers to positioning each pixel of the display after it is manufactured and before leaving the factory to test the brightness, chromaticity, etc. of the pixels, and then performing brightness and chromaticity correction on it. The test positioning of a display is of great significance for the quality control of the display. For example, through accurate test positioning, it can ensure that the test instrument accurately collects various performance data of a specific position on the display. When detecting pixel brightness and color, it can ensure that the measured value is the true value of the specified pixel point, avoiding data inaccuracy caused by position deviation, and providing a reliable basis for subsequent analysis and judgment. In addition, accurate test positioning can comprehensively and carefully detect the performance indicators of each position on the display, timely discover potential problems such as dead pixels, bright pixels, color unevenness, and display abnormalities, which helps to take measures for repair or adjustment in a timely manner during the production process, improving the yield rate of products. Moreover, after accurate test positioning and correction, the display can ensure that during the user's use process, each area can provide a stable, clear, and color-accurate display effect, avoiding display defects or abnormalities and bringing a good visual experience to users.

[0005] The test positioning technology for displays includes, for example, many methods such as physical identification positioning method, coordinate positioning method, image recognition positioning method, laser positioning method, etc. Among these methods, the image recognition positioning method can accurately analyze the feature points and boundaries of specific patterns on the display, thereby achieving high-precision positioning. For example, when performing pixel-level tests, it can accurately find the position of each pixel point, accurately detect the performance of the pixels, and tiny problems such as bad pixels and bright pixels can be accurately located, providing a reliable basis for the quality inspection of the display. In addition, the image recognition positioning method also has many advantages such as non-contact detection, adaptability to complex shapes and diverse tests, obvious advantages in automated testing, rich and traceable data, etc., so it is increasingly applied in the testing of high-end displays such as near-eye displays.

[0006] However, due to the deficiencies of existing display technologies, defects such as non-lit display pixels, low brightness, and uneven brightness often occur in specific areas of the screen (such as the four corners), which brings difficulties to the accurate image recognition and positioning of the display. Summary of the Invention

[0007] Starting from the existing technology, the task of the present invention is to provide a test positioning method, device, storage medium, and method for providing a target image. Through this method or this device, the test positioning accuracy of the display can be significantly improved.

[0008] In the first aspect of the present invention, the aforementioned task is solved by a test positioning method for a display, and the method includes the following steps:

[0009] Display a target image on the display, where the target image includes a plurality of first positioning points and a plurality of second positioning points, where the shape and / or size of the second positioning points are different from those of the first positioning points, and where the second positioning points are at predetermined positions of the target image;

[0010] Take a picture of the displayed target image to obtain a first captured image;

[0011] Identify the second positioning points in the first captured image;

[0012] Determine a homography transformation matrix between the target image and the captured image according to the predetermined positions of the second positioning points in the target image and the actual positions of the second positioning points in the first captured image; and

[0013] Identify the first positioning points in the first captured image, and transform the first positioning points and the second positioning points through the homography transformation matrix to obtain a set of mapping points between the target image and the first captured image.

[0014] In an embodiment of the present invention, the method further includes:

[0015] Display a test image on the display;

[0016] Capture the displayed test image to obtain a second captured image; and

[0017] Obtain the luminance information and / or chrominance information of the test image from the second captured image according to the set of mapping points.

[0018] In another embodiment of the present invention, the target image is rectangular, and the predetermined positions include the four corners of the rectangle, wherein each corner includes a square region with a side length of 1% to 30% of the side length of the rectangle.

[0019] In another embodiment of the present invention, the shape of the second positioning point is different from that of the first positioning point, and the first positioning point is circular, and the shape of the second positioning point is one of the following: triangle, square, rectangle, ellipse, and n-sided polygon, where n≥5.

[0020] In another embodiment of the present invention, the size of the second positioning point is different from that of the first positioning point, wherein the size of the second positioning point is 1.5 to 5 times the size of the first positioning point.

[0021] In another embodiment of the present invention, the size includes: area, diameter, radius, side length, maximum horizontal dimension, or maximum vertical dimension.

[0022] In another embodiment of the present invention, the plurality of second positioning points include at least four second positioning points.

[0023] In another embodiment of the present invention, after determining the homography matrix, the method further includes:

[0024] Correct the first captured image to suppress distortion and / or rotation in the first captured image.

[0025] In another embodiment of the present invention, correcting the first captured image to suppress distortion and / or rotation in the first captured image includes the following steps:

[0026] Capture a distortion correction image without distortion;

[0027] Identify the second positioning points without distortion in the distortion correction image;

[0028] Determine the distortion correction coefficient according to the pixel coordinates of the second positioning points without distortion and the second positioning points with distortion;

[0029] Use the distortion correction coefficient to correct the target image; and

[0030] The corrected target image is displayed by the display.

[0031] In another embodiment of the present invention, the method further includes:

[0032] Sorting the mapping point set according to the sorting rule based on the coordinates of the mapping point set; and

[0033] Interpolating and filling the sorted mapping point set to supplement the missing pixels in the captured image in the tree mapping point set, where the missing pixels are the pixel points that are bright on the target image but not bright in the captured image.

[0034] In another embodiment of the present invention, the method further includes:

[0035] Sorting the mapping point set according to the sorting rule based on the coordinates of the mapping point set; and

[0036] Interpolating and supplementing the sorted mapping point set to supplement the vacant pixels in the mapping point set, where the vacant pixels are the pixel points that should be bright but not bright on the target image.

[0037] In another embodiment of the present invention, the sorting rule includes one of the following:

[0038] Sorting based on Z - shape, sorting based on coordinate mapping, and sorting based on feature matching.

[0039] In another embodiment of the present invention, the sizes of the first positioning point and the second positioning point are different, where the size of the first positioning point is less than a first threshold and the size of the second positioning point is greater than a second threshold, where:

[0040] Identifying the first positioning point in the first captured image includes:

[0041] Extracting, through image recognition, a first graphic in the target image whose size is less than the first threshold; and

[0042] Identifying the first graphic with a size less than the first threshold as the first positioning point; and

[0043] Identifying the second positioning point in the first captured image includes:

[0044] Extracting, through image recognition, a second graphic in the target image whose size is greater than the second threshold; and

[0045] Identifying the second graphic as the second positioning point.

[0046] In another embodiment of the present invention, the first positioning point has a first shape and the second positioning point has a second shape, and the first shape is different from the second shape, wherein:

[0047] Identifying the first positioning point in the first captured image includes:

[0048] Extracting, through image recognition, a first figure having the first shape in the target image; and

[0049] Identifying the first figure as the first positioning point; and

[0050] Identifying the second positioning point in the first captured image includes:

[0051] Extracting, through image recognition, a second figure having the second shape in the target image;

[0052] Identifying the second figure as the second positioning point;

[0053] Determining whether the number of the second positioning points is equal to N.

[0054] In another embodiment of the present invention, the number of the second positioning points is N, where N is a natural number, and identifying the second positioning point in the first captured image further includes:

[0055] Determining whether the number of the second positioning points is equal to N; and

[0056] If so, ending the identification; otherwise, the identification fails.

[0057] In another embodiment of the present invention, the method further includes:

[0058] Fitting the center of the second positioning points in the first captured image; and

[0059] Using the center as a key control point to determine the homography transformation matrix.

[0060] In a second aspect of the present invention, the foregoing task is solved by a test positioning device for a display, the device including:

[0061] A camera configured to capture the displayed target image to obtain a first captured image and capture a test image displayed on the display to obtain a second captured image; and

[0062] A controller configured to perform the following actions:

[0063] Sending an image signal to the display to display the target image thereon, wherein

[0064] The target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and the second positioning points are located at predetermined positions of the target image;

[0065] Identify the second positioning points in the first captured image;

[0066] Determine a homography transformation matrix between the target image and the captured image according to the predetermined positions of the second positioning points in the target image and the actual positions of the second positioning points in the first captured image;

[0067] Identify the second positioning points in the first captured image, and transform the first positioning points and the second positioning points through the homography transformation matrix to obtain a set of mapping points between the target image and the first captured image; and

[0068] Obtain the luminance information and / or chrominance information of the test image according to the set of mapping points from a second captured image.

[0069] In one embodiment of the present invention, the display includes one or more of the following: a waveguide, a computer display, a near-eye display, a virtual reality (VR) display, an augmented reality (AR) display, a smartwatch display, and a smartphone display.

[0070] In another embodiment of the present invention, the display is a micro light-emitting diode display.

[0071] In another embodiment of the present invention, the micro light-emitting diode display includes a micro light-emitting diode chip, and the micro light-emitting diode chip includes:

[0072] A light-emitting mesa;

[0073] An insulating layer that houses the light-emitting mesa and a via contact portion;

[0074] A driving circuit, on the surface of which a metal layer is provided, and a plurality of via contact portions are provided on the driving circuit, the via contact portions are electrically connected to the metal layer, and the micro light-emitting diode array region is bonded to the driving circuit through a bottom conductive bonding layer. The driving circuit further has a wiring stack layer under the metal layer, which leads out a first electrode;

[0075] A first electrode that is electrically connected to the via contact portion;

[0076] A passivation layer that covers at least a part of the side surface of the light-emitting mesa;

[0077] A top transparent conductive layer that is located on the surface of the passivation layer and is in electrical contact with the second epitaxial layer; and

[0078] A second electrode located on the surface of the transparent conductive layer.

[0079] In another embodiment of the present invention, the target image further includes an autofocus pattern for autofocusing between the camera and the display.

[0080] In another embodiment of the present invention, the autofocus pattern includes a set of horizontal lines, a set of vertical lines, a set of oblique lines, and combinations of the above lines.

[0081] In addition, the present invention also provides a computer-readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, performs the following steps:

[0082] Sending a signal to the display to display a target image, wherein the target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and wherein the second positioning points are at predetermined positions in the target image;

[0083] Sending a signal to the camera to capture the displayed target image to obtain a first captured image;

[0084] Identifying the second positioning points in the first captured image;

[0085] Determining a homography transformation matrix between the target image and the captured image based on the predetermined positions of the second positioning points in the target image and the actual positions of the second positioning points in the first captured image; and

[0086] Identifying the second positioning points in the first captured image, and transforming the first positioning points and the second positioning points through the homography transformation matrix to obtain a set of mapping points between the target image and the first captured image.

[0087] In addition, the present invention also provides a test positioning method for a display, which includes the steps of:

[0088] Sending a signal to the display to display a target image, wherein the target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and wherein the second positioning points are at predetermined positions in the target image;

[0089] Sending a signal to the camera to capture the displayed target image to obtain a first captured image;

[0090] Identifying the second positioning points in the first captured image;

[0091] Determine a homography transformation matrix between the target image and the captured image based on the predetermined position of the second positioning point in the target image and the actual position of the second positioning point in the first captured image; and

[0092] Identify the second positioning point in the first captured image, and transform the first positioning point and the second positioning point through the homography transformation matrix to obtain a set of mapping points between the target image and the first captured image.

[0093] In addition, the present invention also provides a method for providing a target image, which includes:

[0094] Generate an image signal for displaying the target image, where the target image includes a plurality of first positioning points and a plurality of second positioning points, where the second positioning points are different in shape and / or size from the first positioning points, and where the second positioning points are at predetermined positions in the target image; and display the image signal.

[0095] In addition, the present invention also provides a target image, including a plurality of first positioning points and a plurality of second positioning points, where the second positioning points are different in shape and / or size from the first positioning points, and where the second positioning points are at predetermined positions in the target image.

[0096] The present invention has at least the following technical effects: The inventor of the present invention found through research that in existing image test positioning, small dots of the same size are used to locate corresponding pixels. However, if small dots are used for shooting, due to the pixel non-uniformity of special displays such as waveguide modules, it is difficult to extract the coordinates of small dots in special areas (especially in the four corners). In the present invention, by using second positioning points that are different in size or shape from the first positioning points to locate pixels in special areas such as corners, even if a certain pixel in a corner is a dead pixel and cannot be lit, or the uniformity is too poor, due to the large area or obvious difference in shape of the bright area, the pixels in these areas can still be accurately located. Using this method greatly improves the robustness of the positioning algorithm in special areas (especially the four corners). Description of the Drawings

[0097] The present invention will be further described below with reference to the accompanying drawings in conjunction with specific embodiments.

[0098] Figure 1 Shows a first embodiment of a target image according to the present invention;

[0099] Figure 2 Shows a second embodiment of a target image according to the present invention;

[0100] Figure 3 Shows a third embodiment of a target image according to the present invention;

[0101] Figure 4Shows the flow of a test positioning method for a display according to the present invention;

[0102] Figure 5 Shows a schematic diagram of a test positioning device for a display according to the present invention; and

[0103] Figure 6 Shows an example of an auto - focus pattern. Detailed implementation manners

[0104] It should be noted that the components in the respective drawings may be exaggerated for illustration purposes and are not necessarily to scale. In the respective drawings, the same or functionally identical components are provided with the same reference numerals.

[0105] In the present invention, unless otherwise specified, "arranged on", "arranged above", and "arranged over" do not exclude the presence of an intermediate object therebetween. In addition, "arranged on or above" only represents the relative positional relationship between two components, and in certain cases, such as after reversing the product direction, it can also be converted to "arranged under or below", and vice versa.

[0106] In the present invention, each embodiment is only intended to illustrate the solution of the present invention and should not be construed as restrictive.

[0107] In the present invention, unless otherwise specified, the quantifiers "a" and "one" do not exclude the scenario of multiple elements.

[0108] In the present invention, the term "connected" can refer to both direct connection between two things and indirect connection between them through an intermediate element.

[0109] In the present invention, the term "configured" means setting the shape, structure, material, and / or function of an object to achieve the desired technical effect, where "configured" includes various alternative technical means for achieving this technical effect, and these technical means become obvious under the teaching of the present invention.

[0110] In the present invention, the controller can be implemented by software, hardware, firmware, or a combination thereof. The controller can exist alone or be a part of a certain component.

[0111] It should also be noted here that, in the embodiments of the present invention, for the sake of clarity and simplicity, only a part of the components or assemblies may be shown. However, those of ordinary skill in the art can understand that, under the teaching of the present invention, the required components or assemblies can be added according to the specific scenario requirements. In addition, unless otherwise specified, the features in different embodiments of the present invention can be combined with each other. For example, a certain feature in the second embodiment can be used to replace the corresponding or functionally identical or similar feature in the first embodiment, and the obtained embodiment also falls within the disclosure scope or the recorded scope of the present application.

[0112] It should also be noted here that within the scope of the present invention, the terms such as "identical", "equal", "equivalent" do not mean that the two values are absolutely equal, but allow a certain reasonable error. That is to say, these terms also cover "substantially identical", "substantially equal", "substantially equivalent". By analogy, in the present invention, the terms indicating directions such as "perpendicular to" and "parallel to" also cover the meanings of "substantially perpendicular to" and "substantially parallel to".

[0113] In the present invention, the term "configured" means setting the shape, structure, material, and / or function of an object to achieve the desired technical effect, where "configured" includes various alternative technical means for achieving this technical effect, and these technical means become obvious under the teaching of the present invention.

[0114] First, the principle on which the present invention is based will be elaborated.

[0115] The present invention is particularly advantageous when applied to a display using an optical shaping device such as an optical waveguide of a near-eye display. Because in a near-eye display, optical devices such as Fresnel lenses, pancake lenses, prisms, free-form surfaces, and optical waveguides will perform shaping operations such as magnifying the displayed image, which may cause pixel distortion and uneven brightness at a predetermined position such as a corner. At this time, if the pixels are located in the traditional way using uniformly sized positioning points, it is easy to cause recognition failure or large errors, which will have a negative impact on subsequent correction and thus damage the user experience. In the present invention, by using a second positioning point with a different size or shape from the first positioning point to locate the pixels in special areas such as corners, even if a certain pixel in one of the four corners is a dead pixel and cannot be lit, or the uniformity is too poor, but due to the large area or obvious difference in shape of the bright area, the pixels in these areas can still be accurately located.

[0116] In addition, the present invention can accurately determine the homography transformation matrix through the second positioning point, which can further reduce the computational complexity of recognition. This is because the position of the predetermined position on the display can be accurately determined in advance, and the second positioning point in the predetermined position can also be accurately recognized in the captured image. Therefore, the homography transformation matrix determined through the correspondence between the two is also of high accuracy. After determining the homography transformation matrix, the first positioning point and the second positioning point can be transformed according to the determined homography transformation matrix to obtain the mapping point set between the target image and the first captured image. In addition, the captured image can be corrected for distortion and rotation by means of the homography transformation matrix. This greatly reduces the correction computational complexity in the subsequent conversion process of the first positioning point and improves the positioning accuracy.

[0117] Thus, through the present invention, the robustness and accuracy of the positioning algorithm in special regions (especially the four corners) are greatly improved.

[0118] The present invention will be further described below with reference to specific embodiments.

[0119] Figure 1 A first embodiment of the target image according to the present invention is shown.

[0120] As Figure 1 shown, the display 200 is divided into a plurality of square virtual grids, where the virtual grids are only for characterizing the pixel block division and do not actually exist. In this embodiment, the display 200 has 16x10 virtual grids, and each virtual grid contains a plurality of pixels, such as 2x2, 8x8, 10x10, 16x16, 256x256, etc. The display 200 can be various types of displays. For example, the display 200 can include a computer display, an optical waveguide, a near-eye display, a virtual reality VR display, an augmented reality AR display, a smartwatch display, and a smartphone display, etc.

[0121] In addition, the display 200 further includes a plurality of predetermined positions 100A-100D (see Figure 1(the dashed boxes in). In this embodiment, the number of the predetermined positions 100A - 100D is four, which are distributed at the four corners of the display 200, and their sizes are as follows: each of the predetermined positions 100A - 100D is a square, and its side length is 1 / 8 of the side length of the display 200. It should be noted that this embodiment is merely exemplary. In other embodiments, the number of the predetermined positions may be more, such as 5, 6, 10, etc.; the sizes of the predetermined positions may be other sizes, such as the side length being 1% - 30% of the side length of the display 200, such as 5%, 10%, 25%, etc. Generally speaking, the predetermined positions contain an integer number of pixels, so their specific sizes can be determined according to the number of pixels. Additionally, in other embodiments, the predetermined positions may be located in the display area other than the corners, for example, they may be located at various positions such as the center position, middle left, middle right, middle up, and middle down.

[0122] The target image 100 is displayed on the display 200. Specifically, the target image 100 displayed on the display 200 includes a plurality of first positioning points 101 and a plurality of second positioning points 102. Here, the shapes of the first positioning points 101 and the second positioning points 102 may be different from each other or be other shapes than circular, such as triangular, square, rectangular, oval, irregular shape, and n-sided shape, where n ≥ 5. The first positioning points 101 may include one or more pixels, such as 1, 10, 16, 32, 64, etc. The second positioning points 102 may include a plurality of pixels, such as 10, 16, 32, 64, etc. The size of the second positioning points 102 is preferably larger than the size of the first positioning points 101. For example, preferably, the size of the second positioning points 102 is 1.2 to 10 times or more, preferably 1.5 to 5 times the size of the first positioning points 101. The sizes of the first positioning points 101 and the second positioning points 102 may be, for example, the radius or diameter, but in other embodiments, the sizes may also include the area, side length, maximum horizontal dimension, or maximum vertical dimension, etc. For example, if the shapes of the first positioning points 101 and the second positioning points 102 are the same and the main difference lies in the size, the area can be used as the distinguishing measure; if the first positioning points 101 and the second positioning points 102 are circular, the radius can be used as the distinguishing measure; if the first and / or second positioning points 101 and 102 are irregular shapes or n-sided shapes (n > 4), the maximum horizontal / vertical dimension / side length can be used as the distinguishing measure.

[0123] The specific positions of the second positioning points 102 in the target image 100 can be determined in advance. For example, each second positioning point 102 is respectively composed of display pixels with corresponding coordinate positions. For example, the second positioning point 102 in the lower left corner can be composed of a first pixel array with n pixels, and its coordinates are respectively (x0, y0), (x1, y1),..., (xn, yn). Since the positions of the second positioning points 102 are known, when all the second positioning points 102 are recognized in the captured image, they can be respectively mapped to the corresponding predetermined positions, and thus to the corresponding coordinate positions on the display 200 or the target image 100. Through the coordinate positions of the second positioning points 102 on the target image 100 and their coordinate positions on the captured image, the homography transformation matrix between the target image 100 and the captured image can be obtained. Additionally, if it is determined that there are distortions or rotations between the second positioning points 102 on the captured image and the second positioning points 102 on the target image, the captured image can be corrected to remove the distortions or rotations. The methods include, for example: First, capture an undistorted distortion correction image and recognize the undistorted second positioning points 102 therein; then determine the distortion correction coefficients according to the pixel coordinates of the undistorted second positioning points 102 and the distorted second positioning points 102 (such as the center or centroid coordinates of the second positioning points 102); then, use the distortion correction coefficients to correct the target image 100; and display the corrected target image by the display 200. For rotations or twists, the same correction method can be used.

[0124] After the homography transformation matrix is determined and the optional correction process is completed, the position data (such as coordinates) of the first positioning points 101 and the second positioning points 102 in the target image 100 can be converted into the position data (such as coordinates) of the first positioning points 101 and the second positioning points 102 in the captured image to form a set of mapping points between the target image and the first captured image. The set of mapping points can include the set of mapping points of all pixels of the first positioning points and the second positioning points, and optionally can include the set of mapping points of other positions in the image. After the set of mapping points is determined, the brightness and / or chromaticity of the subsequent displayed test image can be extracted for brightness and / or chromaticity correction.

[0125] Figure 2 A second embodiment of the target image according to the present invention is shown.

[0126] Figure 2 The second embodiment in Figure 1 is basically the same as the first embodiment in Figure 2 The main difference is that in the second embodiment of Figure 1Compared with the first embodiment, in Figure 2 In the second embodiment, two predetermined positions 100E and 100F at the middle position are added. The layout of the predetermined positions in the second embodiment can more completely cover the border area of the rectangular display 200. In addition, adding two second positioning points 102 can more accurately determine the homography transformation matrix. This is because determining the homography transformation matrix requires 4 positioning points, and adding 2 positioning points can determine multiple homography transformation matrices. Then, the elements of the matrix can be averaged, or the more accurate 4 points among the 6 points can be selected to determine the homography transformation matrix. In addition, when the second positioning point 102 is a square pixel block, during detection, it can be distinguished from the first positioning point 101 by detecting its side length, area, or maximum horizontal / vertical width. In addition, compared with a circle, when the width is the same, a square has a larger area, thus covering more surrounding pixels, so that even if there are bad pixels, chromaticity differences, or brightness differences in these pixels, reliable positioning can still be performed.

[0127] The size of the second positioning point 102 can be determined, for example, through statistical data. The statistical data can, for example, include the distribution probability of bad pixels in each display area in the historical display test data, and then by setting the second positioning point 102 with an appropriate size to cover the area with the highest bad pixel probability. Similarly, the area with the largest chromaticity difference can also be covered by the second positioning point 102 using this method.

[0128] Figure 3 A third embodiment of the target image according to the present invention is shown.

[0129] Figure 3 The third embodiment in Figure 2 is basically the same as the second embodiment in Figure 3 The main difference is that in the third embodiment of

[0130] The target image 100 further includes an autofocus pattern 201. The autofocus pattern 201 can be set in any determined area on the target image 100, preferably at the center of the target image 100.

[0131] The autofocus pattern 201 can be, for example, a pattern including lines, which can measure the image sharpness by using the line pair MTF (modulation transfer function) method, and then determine whether the focusing is correct. A line pair refers to a pair of black and white lines with equal widths. The number of line pairs per millimeter (lp / mm) that can be resolved is the unit for measuring resolution. The more line pairs that can be resolved, the higher the resolution and the higher the potential sharpness of the image. The autofocus process can include, for example: an actuator such as a robotic arm measures the sharpness of the autofocus pattern of the captured image while moving the camera; when the sharpness is greater than or equal to a threshold, it is considered that the focusing is correct, otherwise the camera continues to move. The movement can include, for example, rotating the camera (e.g., around a horizontal axis or a vertical axis or any other axis), and adjusting the distance between the camera and the display, etc.

[0132] Figure 4 The flowchart of the test positioning method for a display according to the present invention is shown. The autofocus pattern 201 can include various forms of lines, such as a horizontal line group, a vertical line group, an oblique line group, and combinations of the above lines.

[0133] An example of the line combination includes:

[0134] (1) A square or rectangular pattern composed of one horizontal line group + three vertical line groups;

[0135] (2) A square or rectangular pattern composed of two horizontal line groups + two vertical line groups. For the specific pattern, see Figure 6 , where it can be seen from Figure 6 that the horizontal line group and the vertical line group are spaced apart from each other respectively. The advantage of doing this is that the horizontal and vertical lines can reference each other to ensure the sharpness in multiple directions, thereby improving the focusing effect.

[0136] (3) A square or rectangular pattern composed of three horizontal line groups + one vertical line group.

[0137] The horizontal line group refers to the lines whose directions are parallel to the horizontal dimension (such as length or width) of the display, the vertical line group refers to the lines whose directions are perpendicular to the horizontal dimension of the display, and the oblique line group refers to the lines whose angles with the horizontal dimension of the display are between 0° and 90°.

[0138] In step 302, a target image is displayed on a display, where the target image includes a plurality of first positioning points and a plurality of second positioning points, where the second positioning points are different in shape and / or size from the first positioning points, and the second positioning points are at predetermined positions in the target image. The positions of the first and second positioning points on the target image are known in advance. For example, the coordinates of each pixel covered by them on the target image can be determined. The display can include various displays, such as a waveguide, a computer monitor, a near-eye display, a virtual reality (VR) display, an augmented reality (AR) display, a smartwatch display, and a smartphone display. The process of the display showing an image can be, for example, that the driving device of the display reads image data, where the image data includes, for example, the brightness and chromaticity of each pixel, and then the display lights up the corresponding pixels according to the image data.

[0139] In step 304, the displayed target image is captured to obtain a first captured image. For example, the displayed target image can be captured by a camera. The camera can include, for example, a digital camera, a webcam, a single-lens reflex camera, etc. The camera is preferably facing the display directly to reduce image distortion or rotation caused by position deviation. The first captured image is, for example, a picture in various formats, such as JPEG, BMP, PNG, AI, TIF, RAW, etc. The picture format contains the brightness and / or chromaticity information of the corresponding pixels generated by the camera sensor.

[0140] In step 306, the second positioning points in the first captured image are identified. This identification process can be achieved, for example, through an image recognition process. For example, first, all circular contours in the target image information are extracted, and the centers of all circular contours are fitted. All circular contours can be traversed, and according to an area threshold, large circular patches and small circular patches are found. The large circular patches are the second positioning points, and the small circular patches are the first positioning points. Here, it can be additionally checked whether the identified second positioning points match their actual number (for example, a natural number N, N = 4, 5, 6...). If so, the identification is completed. If not, the identification fails. Generally speaking, after the identification fails, it may be necessary to check whether there is occlusion in the displayed image, adjust the identification parameters, or perform manual intervention, such as manual annotation.

[0141] In step 308, a homography transformation matrix between the target image and the captured image is determined according to the predetermined positions of the second positioning points in the target image and the actual positions of the second positioning points in the first captured image. For example, the centers of the identified large circular patches are used as key control points to determine the homography transformation matrix. Optionally, an efficient and accurate transformation operation is performed on the image with distortion and rotation angles, so that the original image can be adjusted to a horizontally regular image similar to the target template for subsequent processing. The determination process of the homography transformation matrix is described below.

[0142] First, determine the corresponding points. This requires finding at least 4 sets of corresponding points on two planes (i.e., the target image and the first captured image). These corresponding points can be feature points in the image, such as corner points, edge points, etc., or the positions of known markers. In the present invention, these four feature points are at least four second positioning points here. For example, in image registration, feature points in two images are found through feature extraction algorithms (such as SIFT, SURF, etc.), and then it is determined which points are corresponding through feature matching algorithms.

[0143] Then, construct a system of equations. Let the homography transformation matrix H be a 3x3 matrix:

[0144]

[0145] For a pair of corresponding points (x, y) and (x’, y’), they satisfy the homography transformation relationship:

[0146]

[0147] Expanding the above equation gives two equations:

[0148]

[0149] Rearranging them into the form of linear equations:

[0150]

[0151] Each pair of corresponding points can provide two such equations. Since there are 9 elements, but there is a scale ambiguity (i.e., H and kH represent the same transformation, where k is any non - zero constant), only 8 independent equations need to be determined. Therefore, at least 4 sets of corresponding points are required.

[0152] After obtaining the system of equations constructed from at least 4 sets of corresponding points, various methods can be used to solve the homography transformation matrix. Common methods include the Direct Linear Transformation method (DLT), the least - squares method, etc.

[0153] The obtained homography transformation matrix H may have scale ambiguity and needs to be normalized. Usually, set h 33 to 1, and then divide the other elements by h 33 , to obtain a definite homography transformation matrix:

[0154]

[0155] In step 310, the first positioning point in the first captured image is identified, and the first positioning point and the second positioning point are transformed through the homography matrix to obtain a set of mapping points between the target image and the first captured image. The transformation process is as follows: multiplying the coordinates of the first positioning point and the second positioning point or each of their pixels in the target image by the determined homography matrix can obtain the coordinates of the corresponding pixel points in the first captured image, and then the coordinates are saved in pairs.

[0156] Then, the test image can be displayed on the display and captured to generate a second captured image. According to the set of mapping points, the brightness and / or chromaticity of the corresponding pixels on the test image can be determined, so as to facilitate subsequent brightness and / or chromaticity correction or adjustment.

[0157] Optionally, according to the coordinate relationship of the set of mapping points, the set of points is sorted in a zigzag distribution. The sorted set of points is interpolated and filled, that is, the points with missing pixels (bright points on the target image but not bright points on the captured image) are interpolated and supplemented according to the geometric coordinate relationship. The set of points after the first interpolation and supplementation is interpolated and supplemented with empty pixels (non-bright points on the target image), so as to obtain a dual-channel image with xy coordinate information and the resolution size of the target image. The interpolation method can include, for example: Lagrange interpolation method, Newton interpolation method, piecewise linear interpolation method, cubic spline interpolation method, bilinear interpolation method, etc. The purpose of interpolation is to supplement the pixels that should be lit on the target image and the captured image, so as to obtain a complete set of mapping points.

[0158] Here, in addition to the sorting rule based on the zigzag, sorting based on coordinate mapping and sorting based on feature matching can also be adopted. The following describes these three sorting methods:

[0159] (A) Sorting based on the zigzag: Zigzag sorting is a way of arranging data along a specific zigzag path. Its specific implementation includes, for example, sorting matrix elements or sorting strings by row number. Taking the sorting of matrix elements as an example, if the ordinate of the element is even and the abscissa is 0 or the matrix side length Size - 1, the traversal path is to move one grid horizontally to the right. If the abscissa of the element is even and the ordinate is 0 or Size - 1, the traversal path is to move one grid vertically downward. In addition to the above situations, if the sum of the abscissa and ordinate is even, the traversal path is to move one grid to the upper right corner; if it is odd, it is to move one grid to the lower left corner.

[0160] (B) Sorting based on feature matching: In the feature-based pixel positioning method, for example, the SIFT feature matching algorithm extracts feature points in the image, calculates feature descriptors, and then performs matching and positioning according to the similarity of the feature descriptors. The set of mapping points is determined based on the similarity and spatial relationship of the features.

[0161] (C) Sorting based on coordinate mapping: In some pixel positioning methods based on geometric transformation, such as mapping world coordinates and pixel coordinates through camera calibration, the coordinate relationship of corresponding points is determined according to the principle of projection transformation and geometric relationship in mathematics, and the transformation matrix is calculated.

[0162] In addition, the mapped point set can also be sorted according to methods such as deep learning.

[0163] Figure 5 Fig. shows a schematic diagram of a test positioning device 700 for a display according to the present invention.

[0164] As Figure 5 shown, the test positioning device 700 for a display according to the present invention includes a camera 701 and a controller 703. In addition, the test positioning device 700 may optionally further include a router 704 and a network 705, such as the Internet and an intranet. Each component of the test positioning device 700 will be introduced separately below.

[0165] · The camera 701 is configured to capture a pixel image of the display 702, where the display 702 has a plurality of pixels and is divided into a plurality of sub-regions. The display 702 covers various forms and types of displays, such as monochrome displays, color displays, light-emitting panels, printer printheads, micro light-emitting diode displays, etc. The camera 701 can be a digital camera, a camera, a brightness sensor, a luminance meter, etc.

[0166] · A controller 703, which can be in various forms, such as a central processing unit (CPU), a microcontroller unit (MCU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a personal computer, etc. Here, the controller 703 is shown as a computer. The controller 703 is configured, for example, through software or hardware programming, to determine one or more crosstalk factors based on the captured pixel images. For example, the controller 703 is configured to perform the method according to the present invention. Taking a computer-executable method as an example, the executable method can exist in the form of program instructions and be executed in a processor to perform the method according to the present invention. For example, a test positioning method for a display can be executed on the controller 703, which includes the following steps: First, send a signal to the display to display a target image, where the target image includes a plurality of first positioning points and a plurality of second positioning points, where the second positioning points are different in shape and / or size from the first positioning points, and the second positioning points are at predetermined positions in the target image; then, send a signal to the camera to capture the displayed target image to obtain a first captured image; then, identify the second positioning points in the first captured image; then, determine a homography transformation matrix between the target image and the captured image based on the predetermined positions of the second positioning points in the target image and the actual positions of the second positioning points in the first captured image; and identify the second positioning points in the first captured image, and transform the first positioning points and the second positioning points through the homography transformation matrix to obtain a set of mapping points between the target image and the first captured image. In addition, the controller 703 can also execute a method for providing a target image, which includes the following steps: First, generate an image signal for displaying a target image, where the target image includes a plurality of first positioning points and a plurality of second positioning points, where the second positioning points are different in shape and / or size from the first positioning points, and the second positioning points are at predetermined positions in the target image; then, display the image signal.

[0167] · An optional router 704, which is configured to connect the camera 701 to the network 705. Alternatively, in another application scenario, the router 704 is configured to enable communication between the camera 701 and the controller 703. For example, both the camera 701 and the controller 703 are connected to the router 704, and thus they can communicate directly, either wired or wirelessly. The router 704 can be, for example, a wired router or a Wi-Fi router.

[0168] · An optional network 705, which is configured to enable communication between the controller 703 and the router 704, and further enable communication between the controller 703 and the camera 701. The network 705 can be, for example, the Internet, an intranet, etc. The display 702 is optionally also connected to the network 705 or the router 704, so that the controller 703 can send control signals to the display 702 through the network 705 or the router 704 to light up the corresponding pixels, thereby realizing remote test positioning. Here, the display 702 is connected to the router 704. Of course, the display 702 can also be connected to the controller on-site to achieve direct control.

[0169] In addition, the display 702 can include micro light-emitting diode chips. The display 702 can include various types of displays, such as optical waveguides, computer monitors, near-eye displays, virtual reality (VR) displays, augmented reality (AR) displays, smartwatch displays, and smartphone displays.

[0170] The display 702 will be described below by taking the micro light-emitting diode chip as an example.

[0171] The panel of the display 702 can include micro light-emitting diode chips. A micro light-emitting diode (Micro LightEmitting Diode) is a new type of LED structure obtained by thinning, miniaturizing, and arraying the original LED structure. It integrates arrayed micron-level micro light-emitting diodes on an active addressing driving panel to achieve the lighting and individual control of the micro light-emitting diodes, thereby outputting the desired display image. The core structure of the micro light-emitting diode is the light-emitting mesa, which includes a PN junction diode composed of a direct bandgap semiconductor material. When a forward bias voltage is applied to the micro light-emitting diode between the upper and lower electrodes to cause current to pass through, electrons and holes recombine in the active region, and at the same time, single-color light photons are emitted.

[0172] The micro light-emitting diode chip may include, for example: a light-emitting mesa, an insulating layer, a driving circuit, a first electrode, a passivation layer, a top transparent conductive layer, and a second electrode. The insulating layer is used to accommodate the light-emitting mesa and the via contact portion, and is made of an insulating material such as silicon oxide or silicon nitride. The driving circuit is used to drive the light-emitting diode, and a metal layer is provided on its surface. A plurality of via contact portions are provided on the driving circuit, and the via contact portions are electrically connected to the metal layer. The micro light-emitting diode array region is bonded to the driving circuit through a bottom conductive bonding layer. The driving circuit further has a wiring stack under the metal layer, which leads out the first electrode. The first electrode is electrically connected to the via contact portion. The first electrode is, for example, an anode, which electrically connects the light-emitting mesa to the driving circuit. The passivation layer covers at least a part of the side surface of the light-emitting mesa to protect the light-emitting mesa from metal diffusion of layers such as a mirror layer. The top transparent conductive layer is located on the surface of the passivation layer and is in electrical contact with the second epitaxial layer. The second electrode is located on the surface of the transparent conductive layer. The second electrode is, for example, a cathode.

[0173] The light-emitting mesa includes a first-type epitaxial layer, a second-type epitaxial layer, and a light-emitting layer located therebetween. The first-type epitaxial layer is electrically connected to the ohmic contact layer. The second-type epitaxial layer is electrically connected to the top conductive layer. In some embodiments, the light-emitting mesa of each micro light-emitting diode in the micro light-emitting diode array may be a micron-scale light-emitting mesa. In some embodiments, the micron-scale light-emitting mesa may include, from bottom to top, a first-type epitaxial layer, a light-emitting layer, and a second-type epitaxial layer. That is to say, in the three-layer structure, the first-type epitaxial layer is the closest to the driving circuit; the light-emitting layer is located above the first-type epitaxial layer and is farther from the driving circuit; the second-type epitaxial layer is located above the light-emitting layer and is the farthest from the driving circuit. In some embodiments, the light-emitting layer is formed by a plurality of stacked quantum well layers, especially superlattice-stacked quantum well layers. Preferably, the superlattice-stacked quantum well layers include multiple pairs of quantum well layers stacked with quantum barrier layers. In some embodiments, the first-type epitaxial layer is a semiconductor material of a first conductivity type and includes a plurality of semiconductor layers. The main matrix material of the first-type light-emitting mesa may be, but is not limited to, composed of materials such as Ga, N, As, P, In, or Al. In addition, the first-type epitaxial layer may include, from top to bottom, but is not limited to, a waveguide layer, a confinement layer, a transition layer, and a window layer; in addition, an ohmic contact layer may be formed below the window layer. In some embodiments, the second-type epitaxial layer is a semiconductor material of a second conductivity type and includes a plurality of semiconductor layers. The main matrix material of the second-type epitaxial layer may be, but is not limited to, composed of materials such as Ga, N, As, P, In, or Al. In addition, the second-type epitaxial layer may include, from top to bottom, but is not limited to, a confinement layer and a waveguide layer; in addition, in some embodiments, an ohmic contact layer may be formed on the confinement layer. In one embodiment, the first conductivity type is different from the second conductivity type.

[0174] In one embodiment, the first type of epitaxial layer is an N-type GaN layer or an N-type AlGaN layer, and the second type of epitaxial layer is a P-type GaN layer or a P-type AlGaN layer. That is, the material of the second type of epitaxial layer can be a material layer composed of at least two or more elements of the second conductive type including Ga, N, As, Al, In, and P, and the first type of epitaxial layer can be a material layer composed of at least two or more elements of the first conductive type including Ga, N, As, Al, In, and P. In one embodiment, the light-emitting layer includes a multi-quantum well layer and an electron blocking layer, and the multi-quantum well layer is an InGaN / GaN multi-quantum well layer or an InGaN / AlGaN multi-quantum well layer or an InGaAs / AlGaAs multi-quantum well layer. In another embodiment, the first type of epitaxial layer can also be a P-type GaN layer or a P-type AlGaN layer, and the second type of epitaxial layer is an N-type GaN layer or an N-type AlGaN layer.

[0175] In some embodiments, the light-emitting layer includes at least one quantum well layer. The thickness of the quantum well layer is between 20 nm and 40 nm, for example, the thickness is 30 nm. In some embodiments, the material of the quantum well layer is GaInP / (Al x Ga 1-x ) y In 1-y P, where the range of x is 0.5 to 0.9, and the range of y is 0.3 to 0.5. For example, x is 0.8 and y is 0.5. In some embodiments, the relationship between x and y is that x is 1 to 2 times y. In some embodiments, the light-emitting layer is a multi-quantum well (MQW).

[0176] The size of each micro light-emitting diode chip does not exceed 1 cm, preferably does not exceed 20 microns. The micro light-emitting diode structure is formed in an array form in the micro light-emitting diode chip, and the resolution is, for example, 720*480, 640*480, 1920*1080, 1280*720, 2K or 4K. The diameter of the micro light-emitting diode structure is at the nanometer level, for example, 20 nm to 100 nm.

[0177] In some embodiments of the present invention, the micro light-emitting diode array can include a single-layer micro light-emitting diode structure. In some embodiments of the present invention, the micro light-emitting diode array can include a multi-layer vertically stacked micro light-emitting diode structure.

[0178] In some embodiments of the present invention, the micro light-emitting diode array may include blue micro light-emitting diodes. In some embodiments of the present invention, the pitch of the micro light-emitting diode array, i.e., the minimum center-to-center distance between the micro light-emitting diodes, may be between about 2 micrometers and about 50 micrometers. In some embodiments, the number of pixels on the micro light-emitting diode chip may be between several thousand and several million.

[0179] In one embodiment of the present invention, the driving circuit may be electrically connected to each micro light-emitting diode in the micro light-emitting diode array through separate metal interconnections. In some embodiments, each micro light-emitting diode may be individually electrically controlled by the driving circuit. In some embodiments, the driving circuit may be electrically connected to the electrodes of the micro light-emitting diode chip through metal interconnections. In some embodiments, a dielectric layer may be formed in the gaps between the micro light-emitting diodes. In some embodiments, the dielectric layer may also be formed in the gaps between the interconnections.

[0180] The micro light-emitting diode chip includes a plurality of micro light-emitting diode arrays, and each micro light-emitting diode array includes a plurality of micro light-emitting diodes. The driving method of the micro light-emitting diodes is, for example, passive matrix (PM) driving, in which the cathodes of all the micro light-emitting diodes in each array are commonly connected to the cathode line NL, and the micro light-emitting diodes with the same number in each array are respectively connected to the corresponding anode line PL. Thus, the on / off and light-emitting brightness of each light-emitting diode can be individually controlled by controlling the signals on the corresponding cathode line and anode line.

[0181] Although some embodiments of the present invention have been described in this application document, those skilled in the art can understand that these embodiments are merely shown as examples. Those skilled in the art can conceive of numerous variant schemes, alternative schemes, and improvement schemes under the teaching of the present invention without exceeding the scope of the present invention. The appended claims are intended to define the scope of the present invention and thus cover the methods and structures within the scope of these claims themselves and their equivalent transformations.

Claims

1. A test positioning method for a display, comprising the following steps: Displaying a target image on a display, wherein the target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and wherein the second positioning points are located at predetermined positions of the target image; photographing the displayed target image to obtain a first photographed image; identifying the second positioning point in the first captured image; Determining a homography transformation matrix between the target image and the captured image according to the predetermined position of the second positioning point in the target image and the actual position of the second positioning point in the first captured image; as well as The first positioning point in the first captured image is identified, and the first positioning point and the second positioning point are transformed by the homography transformation matrix to obtain a mapping point set between the target image and the first captured image.

2. The method according to claim 1, further comprising: displaying a test image on the display; photographing the displayed test image to obtain a second photographed image; as well as The brightness information and / or chromaticity information of the test image is acquired according to the second captured image through the mapping point set. 3 . The method according to claim 1 , wherein the target image is a rectangle, and the predetermined position includes four corners of the rectangle, wherein the corners respectively include square areas with sides that are 1% to 30% of the sides of the rectangle.

4. The method according to claim 1, wherein the second positioning point has a different shape from the first positioning point, and the first positioning point is a circle, and the shape of the second positioning point is one of the following: a triangle, a square, a rectangle, an ellipse, and an n-gon, where n≥5. 5 . The method according to claim 1 , wherein the second positioning point has a different size from the first positioning point, wherein the size of the second positioning point is 1.5 to 5 times the size of the first positioning point.

6. The method of claim 5, wherein the size comprises: Area, diameter, radius, side length, maximum horizontal dimension, or maximum vertical dimension. The method according to claim 1 , wherein the plurality of second positioning points comprises at least four second positioning points.

8. The method according to claim 1, after determining the homography transformation matrix, the method further comprises: The first captured image is corrected to suppress distortion and / or rotation in the first captured image.

9. The method according to claim 1, wherein correcting the first captured image to suppress distortion and / or rotation in the first captured image comprises the following steps: Capture distortion-free, distortion-corrected images; identifying a second undistorted positioning point in the distortion-corrected image; Determining a distortion correction coefficient according to pixel coordinates of the second positioning point without distortion and the second positioning point with distortion; Correcting the target image using the distortion correction coefficient; and The calibrated target image is displayed on the monitor.

10. The method according to claim 1, further comprising: According to the coordinates of the mapping point set, the mapping point set is sorted according to a sorting rule; as well as The sorted mapping point set is interpolated and filled to supplement the missing pixels in the captured image into the tree mapping point set, wherein the missing pixels are pixels that are bright in the target image but not bright in the captured image.

11. The method according to claim 10, further comprising: According to the coordinates of the mapping point set, the mapping point set is sorted according to a sorting rule; as well as The sorted mapping point set is interpolated and supplemented to supplement the redundant pixels into the mapping point set, wherein the redundant pixels are pixels on the target image that should be bright but are not.

12. The method according to claim 10 or 11, wherein the sorting rule comprises one of the following: Sorting based on zigzag, sorting based on coordinate mapping, and sorting based on feature matching.

13. The method of claim 1, wherein the first positioning point and the second positioning point have different sizes, wherein the size of the first positioning point is smaller than a first threshold and the size of the second positioning point is larger than a second threshold, wherein: Identifying the first positioning point in the first captured image includes: Extracting a first graphic having a size smaller than a first threshold value from the target image by image recognition; and identifying the first graphic having a size smaller than a first threshold as the first positioning point; and Identifying the second positioning point in the first captured image includes: Extracting a second graphic having a size greater than a second threshold value from the target image by image recognition; and The second graphic is identified as a second positioning point.

14. The method of claim 1, wherein the first positioning point has a first shape and the second positioning point has a second shape, and the first shape is different from the second shape, wherein: Identifying the first positioning point in the first captured image includes: Extracting a first graphic having the first shape in the target image by image recognition; and identifying the first graphic as the first positioning point; and The identifying the second positioning point in the first captured image comprises: Extracting a second graphic having the second shape from the target image through image recognition; identifying the second graphic as a second positioning point; It is determined whether the number of second positioning points is equal to N.

15. The method according to claim 13 or 14, wherein the number of the second positioning points is N, N is a natural number, and wherein the identifying the second positioning points in the first captured image further comprises: Determine whether the number of second positioning points is equal to N; as well as If yes, the recognition ends, otherwise the recognition fails.

16. The method according to claim 1, further comprising: Fitting the center of the second positioning point in the first captured image; as well as The center is used as a key control point to determine the homography transformation matrix.

17. A test positioning device for a display, comprising: a camera configured to capture the displayed target image to obtain a first captured image and to capture the test image displayed on the display to obtain a second captured image; as well as A controller configured to perform the following actions: Sending an image signal to a display to display the target image on the display, wherein the target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and wherein the second positioning points are located at predetermined positions of the target image; identifying the second positioning point in the first captured image; Determining a homography transformation matrix between the target image and the captured image according to the predetermined position of the second positioning point in the target image and the actual position of the second positioning point in the first captured image; Identifying the second positioning point in the first captured image, and transforming the first positioning point and the second positioning point by the homography transformation matrix to obtain a mapping point set between the target image and the first captured image; as well as The brightness information and / or chromaticity information of the test image is acquired according to the second captured image through the mapping point set.

18. The test fixture of claim 17, wherein the display comprises one or more of: an optical waveguide, a computer display, a near-eye display, a virtual reality (VR) display, an augmented reality (AR) display, a smart watch display, and a smartphone display.

19. The test fixture of claim 18, wherein the display is a micro light emitting diode display.

20. The test fixture of claim 17, wherein the target image further comprises an auto focus pattern for auto focus between a camera and a display.

21. The test fixture of claim 19, wherein the auto-focus pattern comprises a horizontal line group, a vertical line group, a diagonal line group, and a combination of the above lines.

22. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the method of claim 1.

23. A target image, comprising: The target image includes a plurality of first positioning points and a plurality of second positioning points, wherein the second positioning points are different in shape and / or size from the first positioning points, and wherein the second positioning points are located at predetermined positions of the target image.

Images