WO2023108545A1

WO2023108545A1 - Method for constructing defect detection model of micro led array panel, apparatures for dectectig pixel defect and devices

Info

Publication number: WO2023108545A1
Application number: PCT/CN2021/138833
Authority: WO
Inventors: Chenchao XU; Yang Yue; Qiming Li
Original assignee: Jade Bird Display (Shanghai)
Priority date: 2021-12-16
Filing date: 2021-12-16
Publication date: 2023-06-22

Abstract

A method for constructing a defect detection model of a micro LED array is provided. The method at least comprises acquiring multiple part-pattern images of the micro LED array by multiple exposure processes, wherein, each exposure process obtains one part-pattern image of the micro LED array; and, the multiple part-pattern images together form a whole micro LED array image.

Description

METHOD FOR CONSTRUCTING DEFECT DETECTION MODEL OF MICRO LED ARRAY PANEL, APPARATURES FOR DECTECTIG PIXEL DEFECT AND DEVICES

FIELD OF THE DISCLOSURE

The present disclosure generally relates to a light emitting diode technology field and, more particularly, to a method for detecting pixel defect of a micro light emitting diode (LED) array panel.

BACKGROUND OF THE DISCLOSURE

Micro LEDs with extra smaller area and higher resolution is increasingly popular in the world. A micro LED array panel can be used to form various kinds of devices, such as camera module, projection modules, display modules, VR/AR optical modules and so on.

However, because the light emitting area and the image displayed by the micro LED array panel are much smaller than before, pixel defects are not easy to be detected and identified by conventional methods. Thus, operators need to review a wafer, a chip and a mask through a graphical user interface displaying various patterns of the micro LED panel, so as to identify the pattern defects.

Unfortunately, the pattern defects of the micro LED array panel cannot be clearly displayed in the patterns via the conventional method.

The above content is only used to assist in understanding the technical solutions of the present application, and does not constitute an admission that the above is prior art.

BRIEF SUMMARY OF THE DISCLOSURE

In order to overcome the drawback mentioned above, the present disclosure provides a method for constructing a defect detection model of a micro LED array panel, so as to improve the pixel detecting accuracy of the micro LED array panel.

To achieve the above objective, the present disclosure provides a method for constructing a defect detection model of a micro LED array, at least comprising:

step 1, acquiring multiple part-pattern images of the micro LED array by multiple exposure processes,

wherein, each exposure process obtains one part-pattern image of the micro LED array; and, the multiple part-pattern images together form a whole micro LED array image.

In some embodiments, step 1 further comprising:

step 101: acquiring N pieces of preset part-patterns of by dividing a whole preset micro LED pattern into N parts, wherein N is a positive integer and more than one;

step 102, switching on pixels in the micro LED array according to a first preset part-pattern;

step 103, acquiring a first part-pattern image by imaging the micro LED array with the switched on pixels; and

step 104, repeating steps 102 and103 to obtain a second part-pattern image, a third part-pattern image, ……, and an Nth part-pattern image.

In some embodiments, in step 101, in every preset part-pattern, one pixel that needs to be switched on is arranged in every N pixels in a row direction and in a column direction; in every preset part-pattern, a first pixel that needs to be switched on in a (N+1) th row is shifted horizontally by one pixel along a second direction, compared to a first pixel that needs to be switched on in a Nth row; and, the pixels that need to be switched on in every preset part-pattern are repeated by every N rows.

In some embodiments, a first pixel that needs to be switched on in a first row of a (N+1) th preset part-pattern is shifted horizontally by at least one pixel along the second direction, compared to a first pixel that needs to be switched on in a first row of a Nth preset part-pattern.

In some embodiments, each preset part-pattern is formed by multiple first-directional parallel lines of pixels at a preset interval along the second direction; and, the preset part-patterns comprise a first preset part-pattern, a second preset part-pattern, ……, and an Nth part-pattern; the Nth preset part-pattern is acquired by shifting the pixels that need to be switched on by at least one pixel compared to the (N-1) th pattern along every row or column in the micro LED array.

In some embodiments, the first direction is different from the second direction.

In some embodiments, the method further comprises:

step 2, acquiring part-pattern image data corresponding to each part-pattern image;

step 3, acquiring whole micro LED array image data by combining all of the part-pattern image data;

step4, obtaining a defect detection model by analyzing and processing the whole micro LED array image data.

In some embodiments, step 4 further includes:

step 401, determining pixel defect points from the whole micro LED array image data not matching a preset feature ; and,

step 402, determining the defect detection model according to the pixel defect points.

In some embodiments, step 401, before determining pixel defect points, further comprising:

performing a normalization processing to the whole micro LED array image data, wherein the whole micro LED array image data includes grayscale values of pixels, and, the preset feature is a grayscale level of a pixel.

In some embodiments, in step 401, the preset feature is a preset threshold value acquired from a user input; and, the normalization processing at least includes analyzing a grayscale distribution of the whole micro LED array image data line by line; and

the step 401 further comprises: classifying the grayscale values of pixels into a normal type and an abnormal type according to the preset feature.

In some embodiments, the abnormal type comprises: a dead pixel, a dark pixel, and an overly bright pixel corresponding to the respective preset threshold values.

In some embodiments, the abnormal type further comprises: a dead area, a dead line, a darkline, a dark area, an overly bright line, and an overly bright area.

In some embodiments, further comprising step 05, displaying a whole defect pattern of the micro LED array according to the micro LED array image data.

In some embodiments, the step 05 further comprises:

displaying pixel grayscale values and defect pixels of the micro LED array on a display screen according to the defect detection model.

In some embodiments, step 05 further comprising: coloring the defective pixels.

In some embodiments, in step 3, after the whole micro LED array image data was obtained, further comprises:

displaying a micro LED pattern image according to the whole micro LED array image data.

In some embodiments, in step 1, each part-pattern image is a binary image or a gray scale image.

In some embodiments, in the step 2, the part-pattern image data is a grayscale image data.

In some embodiments, in the step 1, each of the part-pattern is 1/N of the whole micro LED pattern.

To achieve the above objective, the present disclosure further provides an apparatus for detecting pixel defect of the micro LED array panel, comprising:

an image collecting module, configured to acquire multiple part-pattern images of a micro LED array by multiple exposure processes;

a micro LED control module, configured to control switching-on or switching-off of pixels of the micro LED array;

a pixel defect data processing module, configured to acquire multiple part-pattern image data according to the multiple part-pattern images, and acquire whole micro LED array image data by combining all of the multiple part-pattern image data;

a pixel defect determining module, configured to obtain a defect detection module by analyzing and processing the whole micro LED array image data.

To achieve the above objective, the present disclosure further provides an electronic device comprising: a memory and a processor; wherein,

the memory is used to store at least one computer instruction;

the processor is coupled with the memory for executing the aforementioned.

To achieve the above objective, the present disclosure further provides a non-transitory computer readable medium storing a set of instructions that is executable by one or more processors of a server to cause the server to perform the aforementioned method.

Many other advantages and features of the present disclosure will be further understood by the following detailed descriptions and the appended drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of a method for constructing a defect detection model of the micro LED array panel according to an embodiment of the present disclosure;

FIG. 2 is a flowchart of the step 1 of FIG. 1;

FIG. 3 is a schematic diagram illustrating the multiple part-patterns of the micro LED array according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram illustrating the multiple part-patterns of the micro LED array according to another embodiment of the present disclosure;

FIG. 5 is a block diagram illustrating an apparatus for detecting pixel defect of the micro LED array panel according to an embodiment of the present disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the present preferred embodiments to provide a further understanding of the disclosure. The specific embodiments and the accompanying drawings discussed are merely illustrative of specific ways to make and use the disclosure, and do not limit the scope of the disclosure or the appended claims.

Referring to FIGs. 1 and 2, the method for constructing a defect detection model of a micro LED array panel according to the embodiment comprises the following steps:

step 1, acquiring multiple part-patterns images of a micro LED array in the micro LED array panel by multiple exposure processes; wherein, each exposure process obtains one part-pattern of the micro LED array.

Herein, in the step 1, the multiple part-pattern images may be binary images or grayscale images. Furthermore, each of the part-pattern images is 1/N of a whole micro LED pattern in another embodiment, wherein, N is a positive integer and more than 1.

It is noted that, the micro LED array panel is a micro self-emitting panel. The LED in the panel may be an organic LED or an inorganic LED. The light emitting area of the micro LED array panel is very small, such as 3mm*5 mm. It is noted that, the light emitting area is the area of the micro LED array. The micro LED array panel comprises a micro LED array that forms a pixel array, such as1600×1200, 680×480, 1920×1080. The diameter of the micro LED is in the range of 200nm～2μm. An IC back plane is formed at the back surface of the micro LED array and electrically connected with the micro LED array. The IC back plane acquires signals such as image data from outside via signal lines to control a corresponding micro LED to emit light. The IC back plane generally employs an 8-bit Digital to analog converter (DAC) . The 8-bit DAC has 256 levels of manifestations, and each level corresponds to one gray level, that is, the 8-bit DAC may provide 256 different gray levels. Since any one of the 256 gray levels may be applied on the micro LED, a gray level ranging from 0 to 255 may be displayed by one pixel. Optionally, a brightness value of the micro LED can be controlled by voltage amplitudes or current amplitudes of the signals acquired by the IC back plane, while the gray levels can be shown by time intervals, e.g., pulse widths, of the signals.

Step 1 further comprises the following steps:

step 101: acquiring N pieces of preset part-patterns by dividing a whole preset micro LED pattern into N parts; N is a positive integer and more than one;

Each one of the N pieces of preset part-patterns includes a section of the whole preset micro LED pattern, and the whole preset micro LED pattern is formed by overlapping all of the N pieces of preset part-patterns together.

Referring to FIG. 3, which shows three pieces of preset part-patterns, in every preset part-pattern, each white box represents a pixel which needs to be switched on. In every preset part-pattern, one pixel that needs to be switched on is arranged in every N pixels in a row direction and in a column direction. And, in every preset part-pattern, the first pixel that needs to be switched on in an (N+1) th row is shifted horizontally by one pixel along a second direction (for example, from left to right) , compared to the first pixel that needs to be switched on in an Nth row. Additionally, the pixels that need to be switched on in every preset part-pattern are repeated by every N rows.

Furthermore, the first pixel that needs to be switched on in the first row of the (N+1) th preset part-pattern is shifted horizontally by at least one pixel along the second direction (from left to right) , compared to the first pixel that needs to be switched on in the first row of the Nth preset part-pattern. It is noted that, the preset part-patterns maybe arranged at any sequence; and, the positions of the preset part-patterns can be changed alternatively. The whole preset micro LED pattern can be formed by overlapping the N pieces of the preset part-patterns of pixels together.

In addition, it should be noted that, when detecting pixel defect in the embodiment, in order to ensure that there is no omission in the comprehensive detection, and taking into consideration the detection efficiency and the detection effect, N is preferably selected as three, or any times of three.

For example, the pixels that need to be switched on are arranged in every three pixels in every row and in every column. And, in every preset part-pattern, the first pixel that needs to be switched on in the second row is shifted horizontally by one pixel along the second direction (e.g., from left to right) , compared to the first pixel that needs to be switched on in the first row; the first pixel that needs to be switched on in the third row is shifted horizontally by one pixel along the second direction (e.g., from left to right) , compared to the first pixel that needs to be switched on in the second row; and so forth. Furthermore, the pixels that need to be switched on in the every preset part-pattern are repeated by every three rows. In addition, the first pixel that needs to be switched on in the first row of the second preset part-pattern is shifted horizontally by at least one pixel along the second direction (e.g., from left to right) , compared to the first pixel that needs to be switched on in the first row of the first preset part-pattern; and the first pixel that needs to be switched on in the first row of the third preset part-pattern is shifted horizontally by at least one pixel along the second direction (e.g., from left to right) , compared to the first pixel that needs to be switched on in the first row of the second preset part-pattern.

It is noted that, the patterns in each preset part-pattern are formed by multiple first-directional parallel lines of pixels, and the multiple first-directional parallel lines are arranged at a preset interval along the second direction; and, the preset part-patterns comprises a first preset part-pattern, a second preset part-pattern, ……, and a Nth preset part-pattern; the Nth preset part-pattern is acquired by shifting the pixels that need to be switched on by at least one pixel compared to the (N-1) th preset part-pattern along every row or column in the micro LED array.

Furthermore, the first direction is different from the second direction. Preferably, the N is three and the preset interval is two pixels; or the N is two and the preset interval is one pixels. In the embodiment illustrated in FIG. 3, the preset part-patterns comprise a first preset part-pattern, a second preset part-pattern and a third preset part-pattern. Referring to FIG. 3, the first preset part-pattern, the second preset part-pattern and the third preset part-pattern are arranged in order from left to right, wherein the white boxes represent the pixels that need to be switched on) . In FIG. 3, each one of the big boxes represents a preset part-pattern. Each one of the multiple smaller boxes in the larger boxes represents a pixel of the preset micro LED pattern. The preset first part-pattern comprises multiple parallel lines formed by the white boxes.

It is noted that, the parallel lines can be along any direction in the preset micro LED pattern, for example, the parallel lines can be formed along the row direction, along the column direction, or along the diagonal direction or any other directions in the preset micro LED pattern. Preferably, when the first direction is along the row direction, the second direction is along the column direction, that is to say, the parallel lines move down vertically; or, when the first direction is along the column direction, the second direction is along the row direction, that is to say, the parallel lines shift horizontally; or when the first direction is along any direction except for the row direction, the second direction is along the row direction, that is to say, the parallel lines shift horizontally.

Herein, referring to FIG. 3, take the first direction along the diagonal direction of the big box as an example. The first preset part-pattern comprises a diagonal line in the big box and other lines parallel to the diagonal line at an interval of two pixels along the row direction. In FIG. 3, the parallel lines of the second preset part-pattern shift one pixel along the row direction compared to the parallel lines of the first preset part-pattern, and the parallel lines of the third preset part-pattern shift one pixel along the row direction compared to the parallel lines of the second preset part-pattern. Thus, the first preset part-pattern, the second preset part-pattern and the third preset part-pattern can be overlapped together to form the whole preset micro LED pattern.

Referring to FIG. 4, in another embodiment, the first preset part-pattern in FIG. 4 is as same as the first preset part-pattern in FIG. 3. The difference between the patterns in FIG. 3 and FIG. 4 is as follows:

the second preset part-pattern in FIG. 4 is the third preset part-pattern in FIG. 3; and, the third preset part-pattern in FIG. 4 is the second preset part-pattern in FIG. 3. That is to say, the part-patterns can be arranged in any sequence.

Herein, the pixels are switched on under the control of a control system such as an IC system. The pixels are switched on according to the preset part-patterns, in order from the first preset part-pattern to the Nth preset part-pattern. The detail procedure can be described as follows:

step 102, switching on the pixels in the micro LED array panel according to the first preset part-pattern;

Herein, the pixels are switched on under the control of a control system such as an IC system according to the first preset part-pattern. It is noted that, the pixels can be switched on in a dark room or in any environment.

step 103, acquiring a first part-pattern image by imaging the micro LED array with the switched on pixels;

Herein, the micro LED array in which the pixels are switched on according to the first preset part-pattern is imaged by an optical module (e.g., a charge-coupled device (CCD) camera) to form a first part-pattern image. When the optical module is imaging, there are some pixels with pixel defect in a non-working state, and these pixels cannot emit image light. As a result, in the first part-pattern image, the brightness of a pixel with pixel defect is different from a theoretical brightness of a pixel without defect. In order to obtain this brightness difference, in this embodiment, a binary pattern with a relatively single brightness is used to form the whole preset micro LED pattern, based on which the first present part-pattern image is formed. The pixels in the binary pattern has only two kinds of brightness, and the brightness difference after imaging is more obvious, which is advantageous in detecting pixel defect according to pixel brightness.

In some embodiments, the first part-pattern image may be a binary image. The pixels in the binary image have only two kinds of brightness, e.g., black or white.

In some other embodiments, the first part-pattern image may be a grayscale image. A grayscale camera can be directly used to collect the image obtained by switching on the pixels in the micro LED array according to the first present part-pattern, and then the grayscale image can be obtained; or after a color camera is used for shooting, the obtained image is subjected to graying, which is not limited in this embodiment.

Different from the binary image, the grayscale image includes black, white and multiple different gray levels between black and white. The gray level can express the brightness of the first part-pattern image, for example, white means the brightest and black means the darkest. Therefore, based on the brightness of the pixels shown in the grayscale first part-pattern image, it can be determined which pixel in the micro LED array does not emit image light. It should be understood that the use of “first” to define the first part-pattern is only for the convenience of description and does not constitute any limitation to the present disclosure.

step 104, repeating the

steps

102 and 103 to obtain the second part-pattern image, then, the third part-pattern image, ……, and the Nth part-pattern image. Herein, preferably, N is three in this embodiment.

Herein, the part-pattern image data includes data of each pixel in the part-pattern image. In the step 2, as mentioned above in step 1, the part-pattern image data may be binary image data or grayscale image data.

step 3, acquiring a whole micro LED array image data by combining all of the part-pattern image data;

The whole micro LED array image data includes data of each pixel in a whole micro LED array image.

For example, data of a pixel in the whole micro LED array image data is obtained by combining data of corresponding pixels of all of the part-pattern image data. Taken FIG. 3 as an example, a grayscale value of the left-most pixel in the top-most row of the whole micro LED array image data is obtained by summing a first grayscale value of the left-most pixel in the top-most row of the first part-pattern image data, a second grayscale value of the left-most pixel in the top-most row of the second part-pattern image data, and a third grayscale value of the left-most pixel in the top-most row of the third part-pattern image data.

Herein, in the step 3, after the whole micro LED array image data was obtained, further comprises: displaying a micro LED pattern image according to the whole micro LED array image data. The micro LED pattern image is a grayscale image.

step 4, obtaining a defect detection model by analyzing and processing the whole micro LED array image data.

Herein, the step 4 further comprises the following steps:

step 401, determining pixel defect points not matching a preset feature ofthe whole micro LED array image data;

Herein, in the step 401, before determining pixel defect points, further comprising: performing a normalization processing to the whole micro LED array image data; and, the micro LED array image data comprises grayscale values of pixels; and, the preset feature is a preset grayscale value of each pixel.

Furthermore, in the step 401, the preset feature be a preset threshold values acquired from a user input; and, the normalization processing at least includes analyzing a grayscale distribution of the whole micro LED array image data line by line.

The pixel defects with a grayscale difference from the preset feature are determined based on the grayscale distribution. In the step 401, the grayscale distribution is the brightness change of the grayscale image data of the micro LED array. When analyzing the gray distribution of the grayscale image data line by line, edge detection operators can be used, such as Roberts cross operator, Prewitt operator, Sobel operator, Kirsch operator, compass operator, Canny operator and /or Laplacian Operators, etc., to detect a pixel with larger brightness changer in each pixel row of the grayscale imagedata, and use them as pixel located on the boundary in each pixel row.

The step 401 further comprises: classifying the pixel grayscale values into a normal type and an abnormal type according to the preset feature; wherein, the abnormal type comprises a dead pixel, a dark pixel, and an overly bright pixel corresponding to the respective preset threshold values. The preset threshold values comprise several thresholds such as a first threshold, a second threshold and so on. For example, the pixel value as zero is a dead point; the pixel value less than the first threshold is a dark point; the pixel value between the first threshold and the second threshold is a normal point; and the pixel value more than the second threshold is an overly bright point. It is noted that, the various preset threshold values are empirical values. Taking an 8-bit image as an example, the first set threshold may be 40 and the second set threshold may be 60. Of course, the above values are for example only, and are not limited in practice.

step 402, determining the defect detection model of the micro LED array panel according to the pixel defect points.

Additionally, a defect detection model comprises different pixel types corresponding to each pixel. The abnormal type further comprises: a dead area, a dead line, a dark line, a dark area, an overly bright line, and an overly bright area. After determining the pixel defect point on the grayscale image of the whole micro LED array, at least one contour of the pixel defect area or the pixel defect line composed of the defect points can be determined according to the coordinate of each pixel defect point in the grayscale image of the whole micro LED array.

It can be understood that, the defect area or the defect line has a specific grayscale feature and the grayscale feature is associated with the gray level of the grayscale image. The pixel brightness of the defect area is close to or equal to a same grayscale, such as close to black or close to a grayscale value being less than 20.

step 05, displaying a whole defect pattern of the micro LED array panel according to the micro LED array image data.

Herein, the step 05 further comprises the following steps: displaying the pixel grayscale values and defective pixels of the micro LED array panel on a display screen according to the defect detection model.

Herein, the defective pixels with pixel grayscale values are displayed on the display screen. Additionally, step 05further comprises: coloring the defective pixels and showing the colored pixel defects on the display screen. Herein, the defective pixels comprise different type of defects, such as dark, dead, overly bright. Thus, the color of the different defective pixels is different from each other, while the color of the defective pixels with the same defect type is same.

Referring to FIG. 5, an apparatus for detecting pixel defect of the micro LED array panel is further provided in the embodiment of the present disclosure. The apparatus comprises:

a micro LED control module, configured to control the switching-on or switching-off of the pixels in the micro LED array;

a pixel defect data processing module, configured to acquire part-pattern image data, and acquire whole micro LED array image data by combining all of the part-pattern image data;

a pixel defect determining module, configured to obtain a defect detection mode by analyzing and processing the whole micro LED array image data.

Herein, the pixel defect data processing module is specifically configured to the aforementioned step 1, which will not be described herein anymore.

Furthermore, an electronic device comprises a memory and a processor is provided in the embodiment. Wherein, the memory is used to store at least one computer instruction; and, the processor is coupled with the memory for executing the aforementioned method.

A non-transitory computer readable medium is further provided in the embodiment. The medium stores a set of instructions that is executable by one or more processors of a server to cause the server to perform the aforementioned method.

The above descriptions are merely embodiments of the present disclosure, and the present disclosure is not limited thereto. A modifications, equivalent substitutions and improvements made without departing from the conception and principle of the present disclosure shall fall within the protection scope of the present disclosure.

Claims

A method for constructing a defect detection model of a micro LED pixel array, at least comprising:

step 1, acquiring multiple part-pattern images of the micro LED array by multiple exposure processes,

wherein, each exposure process obtains one part-pattern image of the micro LED array; and, the multiple part-pattern images together form a whole micro LED array image.
The method according to claim 1, wherein, step 1 further comprising:

step 101: acquiring N pieces of preset part-patterns of by dividing a whole preset micro LED pattern into N parts, wherein N is a positive integer and more than one;

step 102, switching on pixels in the micro LED array according to a first preset part-pattern;

step 103, acquiring a first part-pattern image by imaging the micro LED array with the switched on pixels; and

step 104, repeating steps 102 and103 to obtain a second part-pattern image, a third part-pattern image, ……, and an Nth part-pattern image.
The method according to claim 2, wherein, in step 101, in every preset part-pattern, one pixel that needs to be switched on is arranged in every N pixels in a row direction and in a column direction; in every preset part-pattern, a first pixel that needs to be switched on in a (N+1) th row is shifted horizontally by one pixel along a second direction, compared to a first pixel that needs to be switched on in a Nth row; and, the pixels that need to be switched on in every preset part-pattern are repeated by every N rows.
The method according to claim 3, wherein, a first pixel that needs to be switched on in a first row of a (N+1) th preset part-pattern is shifted horizontally by at least one pixel along the second direction, compared to a first pixel that needs to be switched on in a first row of a Nth preset part-pattern.
The method according to claim 4, wherein, N is three.
The method according to claim 4, wherein, each preset part-pattern is formed by multiple first-directional parallel lines of pixels at a preset interval along the second direction; and, the preset part-patterns comprise a first preset part-pattern, a second preset part-pattern, ……, and an Nth part-pattern; the Nth preset part-pattern is acquired by shifting the pixels that need to be switched on by at least one pixel compared to the (N-1) th pattern along every row or column in the micro LED array.
The method according to claim 6, wherein, the first direction is different from the second direction.
The method according to claim 1, wherein, the method further comprises:

step 2, acquiring part-pattern image data corresponding to each part-pattern image;

step 3, acquiring whole micro LED array image data by combining all of the part-pattern image data;

step4, obtaining a defect detection model by analyzing and processing the whole micro LED array image data.
The method according to claim 8, wherein, step 4 further includes:

step 401, determining pixel defect points from the whole micro LED array image data not matching a preset feature ; and,

step 402, determining the defect detection model according to the pixel defect points.
The method according to claim9, wherein, step 401, before determining pixel defect points, further comprising:

performing a normalization processing to the whole micro LED array image data, wherein the whole micro LED array image data includes grayscale values of pixels, and, the preset feature is a grayscale level of a pixel.
The method according to claim 10, wherein, in step 401, the preset feature is a preset threshold value acquired from a user input; and, the normalization processing at least includes analyzing a grayscale distribution of the whole micro LED array image data line by line; and

the step 401 further comprises: classifying the grayscale values of pixels into a normal type and an abnormal type according to the preset feature.
The method according to claim 11, wherein, the abnormal type comprises: a dead pixel, a dark pixel, and an overly bright pixel corresponding to the respective preset threshold values.
The method according to claim 11, wherein, the abnormal type further comprises: a dead area, a dead line, a dark line, a dark area, an overly bright line, and an overly bright area.
The method according to claim 8, wherein, further comprising step 05, displaying a whole defect pattern of the micro LED array according to the micro LED array image data.
The method according to claim 14, wherein, the step 05 further comprises:

displaying pixel grayscale values and defect pixels of the micro LED array on a display screen according to the defect detection model.
The method according to claim 14, wherein, in the step 05 further comprising: coloring the defective pixels.
The method according to claim 8, wherein, in step 3, after the whole micro LED array image data was obtained, further comprises:

displaying a micro LED pattern image according to the whole micro LED array image data.
The method according to claim 1, wherein, in step 1, each part-pattern image is a binary image or a gray scale image.
The method according to claim 8, wherein, in the step 2, the part-pattern image data is a grayscale image data.
The method according to claim 1, wherein, in the step 1, each of the part-pattern is 1/N of the whole micro LED pattern.
An apparatus for detecting pixel defect of the micro LED array panel, comprising:

an image collecting module, configured to acquire multiple part-pattern images of a micro LED array by multiple exposure processes;

a micro LED control module, configured to control switching-on or switching-off of pixels of the micro LED array;

a pixel defect data processing module, configured to acquire multiple part-pattern image data according to the multiple part-pattern images, and acquire whole micro LED array image data by combining all of the multiple part-pattern image data;

a pixel defect determining module, configured to obtain a defect detection module by analyzing and processing the whole micro LED array image data.
An electronic device, comprising: a memory and a processor; wherein,

the memory is used to store at least one computer instruction;

the processor is coupled with the memory for executing the method of the claim1.
A non-transitory computer readable medium storing a set of instructions that is executable by one or more processors of a server to cause the server to perform the method of the claim 1.