WO2021189259A1

WO2021189259A1 - Oled screen point defect determination method and apparatus, storage medium and electronic device

Info

Publication number: WO2021189259A1
Application number: PCT/CN2020/080945
Authority: WO
Inventors: 王帅; 姜立
Original assignee: 京东方科技集团股份有限公司
Priority date: 2020-03-24
Filing date: 2020-03-24
Publication date: 2021-09-30
Also published as: CN113785181A

Abstract

The present application provides an OLED screen point defect determination method and apparatus, a storage medium and an electronic device. The method comprises: acquiring an image of an OLED screen; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; identifying the contour size of a defect position of OLED screen points according to image features of the Y image, and taking the contour size as a contour feature; and performing defect determination on the OLED screen points according to the contour feature. The present application can improve OLED screen defect point detecting efficiency, increase detecting speed, and improve a defect point detecting effect.

Description

Method, device, storage medium and electronic equipment for determining point defect of OLED screen

Technical field

This application relates to the technical field of electronic equipment, and in particular to a method, device, storage medium and electronic equipment for determining point defects of OLED screens.

Background technique

Defect point detection is an indispensable part of the display screen manufacturing process. An efficient and accurate defect point detection method can not only detect defective products, improve the quality of display screen shipments, but also save costs and improve corporate efficiency.

The defect detection methods in related technologies mainly rely on manual detection.

In this way, the defect point detection efficiency is low, the detection speed is slow, and the defect point detection effect is not good.

Summary of the invention

This application aims to solve one of the technical problems in the related technology at least to a certain extent.

To this end, the present application is to propose a method, device, storage medium and electronic equipment for determining point defects of OLED screens, which can improve the efficiency of defect detection of OLED screens, increase the detection speed, and improve the effect of defect detection.

In order to achieve the above objective, the method for determining point defects of an OLED screen proposed by the embodiment of the first aspect of the present application includes: acquiring an image of the OLED screen; converting the image into a YUV image, and extracting the Y image corresponding to the YUV image; The image feature of the Y image identifies the outline size of the defect position of the OLED screen point, and uses the outline size as the outline feature; and performs defect judgment on the OLED screen point according to the outline feature.

The method for determining the point defect of the OLED screen proposed by the embodiment of the first aspect of the application is to obtain an image of the OLED screen; convert the image to a YUV image, and extract the Y image corresponding to the YUV image; identify the OLED screen point according to the image characteristics of the Y image The contour size of the defect position is used as the contour feature; the defect judgment of the OLED screen point according to the contour feature can improve the defect detection efficiency of the OLED screen, increase the detection speed, and improve the defect detection effect.

In order to achieve the above purpose, the device for determining the point defect of the OLED screen proposed in the embodiment of the second aspect of the present application includes: an acquisition module for acquiring an image of the OLED screen; a conversion module for converting the image into a YUV image and extracting The Y image corresponding to the YUV image; an identification module, used to identify the outline size of the defect position of the OLED screen point according to the image characteristics of the Y image, and use the outline size as the outline feature; the determination module uses Based on the outline feature, the defect judgment of the OLED screen dot is performed.

The device for determining the point defect of the OLED screen proposed by the embodiment of the second aspect of the present application acquires an image of the OLED screen; converts the image into a YUV image, and extracts the Y image corresponding to the YUV image; and identifies the OLED screen point according to the image characteristics of the Y image The contour size of the defect position is used as the contour feature; the defect judgment of the OLED screen point according to the contour feature can improve the defect detection efficiency of the OLED screen, increase the detection speed, and improve the defect detection effect.

The non-transitory computer-readable storage medium proposed by the embodiment of the third aspect of the present application, when the instructions in the storage medium are executed by the processor of the electronic device, enables the electronic device to execute a method for determining point defects of OLED screens, The method includes: the point defect determination method of the OLED screen proposed by the embodiment of the first aspect of the present application.

The non-temporary computer-readable storage medium proposed by the embodiment of the third aspect of the present application acquires an image of an OLED screen; converts the image into a YUV image, and extracts the Y image corresponding to the YUV image; recognizes the OLED according to the image characteristics of the Y image The contour size of the defect position of the screen point, and the contour size is used as the contour feature; the defect judgment of the OLED screen point according to the contour feature can improve the defect detection efficiency of the OLED screen, increase the detection speed, and improve the defect detection effect.

The electronic device proposed by the embodiment of the fourth aspect of the present application includes: a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is arranged inside a space enclosed by the housing, The processor and the memory are arranged on the circuit board; the power supply circuit is used to supply power to various circuits or devices of the electronic equipment; the memory is used to store executable program codes; the processor The program corresponding to the executable program code is run by reading the executable program code stored in the memory, so as to execute the OLED screen point defect determination method proposed in the embodiment of the first aspect of the present application.

The electronic device proposed in the embodiment of the fourth aspect of the present application acquires an image of the OLED screen; converts the image into a YUV image, and extracts the Y image corresponding to the YUV image; according to the image characteristics of the Y image, it can identify the defect location of the OLED screen point Contour size, and use the contour size as the contour feature; according to the contour feature to determine the defect of the OLED screen point, it can improve the defect detection efficiency of the OLED screen, increase the detection speed, and improve the defect detection effect.

The additional aspects and advantages of this application will be partly given in the following description, and some will become obvious from the following description, or be understood through the practice of this application.

Description of the drawings

The above and/or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the accompanying drawings, in which:

FIG. 1 is a schematic flowchart of a method for determining point defects of an OLED screen according to an embodiment of the present application;

2 is a schematic diagram of an image of an OLED screen according to an embodiment of the application;

Figure 3 is a schematic diagram of a Y image in an embodiment of the application;

4 is a schematic flowchart of a method for determining point defects of an OLED screen proposed by another embodiment of the present application;

5 is a schematic diagram of a pixel distribution curve diagram according to an embodiment of the application;

FIG. 6 is a schematic diagram of converting a Y image into a binary image according to an embodiment of the application;

FIG. 7 is a schematic diagram of a target binary image according to an embodiment of the application;

FIG. 8 is a schematic diagram of point defects of an OLED screen in an embodiment of the application;

FIG. 9 is a schematic structural diagram of an OLED screen point defect determination device provided by an embodiment of the present application;

FIG. 10 is a schematic structural diagram of a point defect determination device for an OLED screen according to another embodiment of the present application;

FIG. 11 is a schematic structural diagram of an electronic device proposed in an embodiment of the present application.

Detailed ways

The embodiments of the present application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the drawings are exemplary, and are only used to explain the present application, and should not be construed as a limitation to the present application. On the contrary, the embodiments of the present application include all changes, modifications and equivalents falling within the scope of the spirit and connotation of the appended claims.

FIG. 1 is a schematic flowchart of a method for determining point defects of an OLED screen proposed by an embodiment of the present application.

In this embodiment, the OLED screen point defect determination method is configured as an OLED screen point defect determination device for example.

Among them, the OLED screen is an organic light-emitting semiconductor (Organic Light-Emitting Diode, OLED) screen.

The OLED screen point defect determination method in this embodiment may be configured in the OLED screen point defect determination device, and the OLED screen point defect determination device may be set in the server or may also be set in the electronic device. This embodiment of the application does not do this. limit.

In this embodiment, the point defect determination method of an OLED screen is configured in an electronic device as an example.

It should be noted that the execution subject of the embodiments of the present application may be, for example, a server or a central processing unit (CPU) in an electronic device in hardware, and may be, for example, a server or a related processor in an electronic device in software. There is no restriction on the background service.

Referring to Figure 1, the method includes:

S101: Obtain an image of the OLED screen.

Considering that the defective points of the screen have differences in display brightness, the boundary between the normal points and the defective points of the screen will form a bright and dark contour line. The difference in display brightness can be reflected in the image of the screen. Therefore, this application The embodiment can use the image of the OLED screen to determine the defects of the screen dots, and can effectively use the image characteristics of the screen defect dots, so that the judgment result is more accurate.

When acquiring the image of the OLED screen described above, the device (such as a mobile terminal, a video camera, etc.) with an image acquisition function may specifically capture a picture displayed on the screen and use it as an image of the screen, which is not limited.

Refer to Figure 2, which is a schematic diagram of an image of an OLED screen according to an embodiment of the application, which includes a plurality of screen points. The point defect determination method of the OLED screen in the embodiment of the invention is used to determine whether each screen point is a defect point. When it is judged as a defect point, the position information of the defect point can be determined, and the number of screen defect points can be counted.

The image of the OLED screen obtained above can be recorded as I1. When I1 is obtained, I1 can be input to the electronic device that executes the OLED screen point defect determination method, and the electronic device automatically determines the defect of the screen point.

The above-mentioned image of the OLED screen may be an original image obtained by shooting, and the original image may be, for example, a RAW format image without any processing that is collected by an image sensor of an electronic device, and there is no limitation on this.

Among them, the RAW format image is the original image that the image sensor converts the captured light source signal into a digital signal.

S102: Convert the image into a YUV image, and extract a Y image corresponding to the YUV image.

S103: According to the image feature of the Y image, identify the outline size of the defect position of the OLED screen point, and use the outline size as the outline feature.

In some embodiments, the image feature can be, for example, the brightness, grayscale, chroma, saturation and other features of the image. Therefore, the corresponding brightness, grayscale, chroma, saturation and other features can be combined to identify the screen points. Defective points, alternatively, any other possible image features can be combined to identify defective points, and there is no restriction on this.

In the embodiment of the present application, when identifying the contour feature of the defect position of the OLED screen according to the image feature of the image, the image can be converted into a YUV image, and the Y image corresponding to the YUV image is extracted, and the identification is based on the image feature of the Y image. The outline feature of the defect location of the OLED screen point, by extracting the gray image of the image of the OLED screen, can effectively assist the subsequent identification of the OLED screen defect point, and improve the recognition accuracy of the screen defect point.

Refer to Fig. 3, which is a schematic diagram of a Y image in an embodiment of the application.

The above-mentioned YUV image refers to an image that can be processed by the display of an electronic device, and the image format is an image in the YUV format.

Among them, the luminance signal of the image is called Y, and the chrominance signal is composed of two independent signals. Depending on the color system and format, the two chrominance signals are often called U and V. In this case, after the image of the OLED screen is obtained, the image can be converted into a YUV image by an image signal processor (Image Signal Processing, ISP), and the Y image corresponding to the YUV image can be extracted, and the OLED screen can be identified according to the image characteristics of the Y image The contour feature of the defect location of the point.

S104: Perform defect judgment on the OLED screen dots according to the contour characteristics.

After identifying the outline feature of the defect position of the OLED screen point, the outline feature can be compared with the set feature threshold. When the result of the comparison between the outline feature and the set feature threshold meets the condition, it is determined that the outline feature corresponds to The screen point of the defect position is a defect point, and the position information of the defect point is recorded, and there is no restriction on this.

In this embodiment, the image of the OLED screen is acquired; the image is converted into a YUV image, and the Y image corresponding to the YUV image is extracted; according to the image characteristics of the Y image, the outline size of the defect location of the OLED screen is identified, and the outline size As a contour feature: Defect judgment of OLED screen points based on contour features can improve the efficiency of defect detection of OLED screens, increase detection speed, and improve defect detection effects.

4 is a schematic flowchart of a method for determining point defects of an OLED screen according to another embodiment of the present application.

Referring to Figure 4, the method includes:

In the description steps of this embodiment, reference may be made to Figs. 2 and 3 described above.

Referring to Figure 4, the method includes:

S401: Obtain an image of the OLED screen.

S402: Convert the image into a YUV image, and extract a Y image corresponding to the YUV image.

S403: Convert the Y image into a binary image according to the image characteristics of the Y image.

Optionally, according to the image characteristics of the Y image, the Y image is converted into a binary image, which can be to traverse each pixel of the Y image, determine the number of pixels with different gray values, and according to the number of pixels with different gray values , To form a pixel distribution curve, determine the pixel gray threshold according to the pixel distribution curve, compare the gray value of each pixel with the pixel gray threshold, and convert the Y image into a binary image according to the result of the comparison .

The above-mentioned binary image (Binary Image) means that each pixel on the image has only two possible values or gray levels. Usually black and white, B&W, and monochrome images are used to represent the binary image, and the image is binarized. The function is to facilitate the extraction of information in the image, and the binary image can increase the recognition efficiency during computer recognition.

Referring to FIGS. 5 and 6, FIG. 5 is a schematic diagram of a pixel distribution curve diagram according to an embodiment of the application, and I3 is used to represent the pixel distribution curve diagram, and FIG. 6 is a schematic diagram of converting a Y image into a binary image according to an embodiment of the application.

As an example, traverse each pixel in the Y image I2, count the number of pixels corresponding to different gray values in the Y image I2, and get the pixel distribution curve I3, because the number of defective points is orders of magnitude compared to the number of normal pixels Therefore, the defective point should be located at the extreme value of the curve, and the pixel gray threshold can be calculated according to the above-mentioned pixel distribution curve I3, so that the pixel gray threshold is used as the judgment condition to traverse all the pixels of the image, and the gray value is lower than the pixel The grayscale of the pixel with the grayscale threshold is set to 255 (full white), and the grayscale of the pixel with a grayscale value higher than the pixel gray threshold is set to 0 (full black), forming a binary image I4.

By traversing each pixel of the Y image, the number of pixels with different gray values is determined, and the pixel distribution curve is formed according to the number of pixels with different gray values. The pixel gray threshold is determined according to the pixel distribution curve, and each pixel The gray value of the point is compared with the pixel gray threshold, and the Y image is converted into a binary image according to the result of the comparison. This provides a convenient and fast method to obtain a binary image, which can be determined adaptively Threshold, and make the obtained binary image can better show the difference between the normal point and the defective point of the screen image.

S404: Perform morphological processing on the binary image to obtain a target binary image.

Optionally, morphological processing is performed on the binary image to obtain the target binary image, which may be to use structural elements of the first size to perform corrosion processing on the binary image, and to use structural elements of the second size to perform corrosion processing on the two-valued image. Perform expansion processing on the value image, and use the structural elements of the third size to perform corrosion processing on the expanded binary image again to obtain the target binary image. The first size, second size, and third size can be the same or different .

The above-mentioned first size a1*a1, second size a2*a2, and third size a3*a3 can be adjusted according to the size and resolution of the image capture device and the panel. Generally, the value range of a1, a2, and a3 belongs to [3, 7] For this embodiment, a1=5, a2=3, and a3=3, and there is no restriction on this.

The above-mentioned target binary image can be expressed as I5, see FIG. 7, which is a schematic diagram of the target binary image according to an embodiment of the application.

The above-mentioned structure elements of the first size are used to perform corrosion processing on the binary image, the structure elements of the second size are used to perform expansion processing on the binary image after the corrosion processing, and the structure elements of the third size are used to perform the expansion processing on the two-value image. The value image is corroded again to obtain the target binary image, which provides an effective method to remove the interference points of the screen image, denoises the screen image, reduces the computing resources required for identification, and guarantees subsequent screen defects The recognition effect.

S405: Identify the outline size of the defect position of the OLED screen point according to the target binary image, and use the outline size as the outline feature.

Optionally, identifying the outline size of the defect location of the OLED screen point according to the target binary image can be based on the target binary image, determining the outline set of the defect location of the OLED screen point, and traversing each element of the outline set, Recognizing the outline rectangles, forming a set of outline rectangles, and using the length and width of each outline rectangle in the set of outline rectangles as the outline size, it can effectively identify the characteristics of the outline boundary line at the boundary between the normal point and the defect point. Realize the contour recognition and positioning of the screen point defect position.

S406: Retain the contour rectangles whose length and width are greater than the set threshold in the contour rectangle set.

S407: Form a point defect set according to the retained contour rectangles and the coordinate information corresponding to each contour rectangle.

As an example, the outline set of the defect position of the OLED screen point can be determined according to the target binary image I5, and the screen point corresponding to the defect position can be a suspected defect point. Therefore, the outline set can be regarded as The contour line set of the suspected point, and then each element in the contour line set can be traversed to determine the contour line rectangle to form the contour line rectangle set, which is determined according to the length and width of each contour line rectangle in the contour line rectangle set Whether the corresponding screen point is a defect point.

Optionally, determine whether the corresponding screen point is a defect point according to the length and width of each contour rectangle in the contour rectangle set. When the length and width are both smaller than a4, then the contour rectangle is collected from the contour rectangle Delete, otherwise keep, the contour line rectangle set after the traversal is completed, and the point defect set is formed according to the reserved contour line rectangle and the coordinate information corresponding to each contour line rectangle.

It should be noted that the size of a4 can be adjusted according to the size and resolution of the image capture device and the panel. For this embodiment, a4=4, which is not limited.

S408: Determine the number of point defects and the location information of each point defect according to the point defect collection.

After the point defect set is obtained, the number of point defects in the point defect set and the location information of each point defect can be counted, thereby completing the point defect judgment of the OLED screen.

Refer to FIG. 8, which is a schematic diagram of a point defect of an OLED screen in an embodiment of the application. Fig. 8 is the output result of the design algorithm based on the flowchart shown in Fig. 4. Through this application, the purpose of determining the number and location of OLED screen point defects can be achieved, so as to solve the problem that a large number of point defects cannot be quantitatively described, and for large-size printing OLED The bad judgment of the display screen provides technical support, effectively identifies the defects of the screen points, and obtains the number and location information of the defect points, which can effectively guide the production staff to improve the screen, enhance the recognition effect, and enrich the recognition content.

In this embodiment, the image of the OLED screen is acquired; the image is converted into a YUV image, and the Y image corresponding to the YUV image is extracted; according to the image characteristics of the Y image, the outline size of the defect location of the OLED screen is identified, and the outline size As a contour feature: Defect judgment of OLED screen points based on contour features can improve the efficiency of defect detection of OLED screens, increase detection speed, and improve defect detection effects. Provides a convenient and fast method for obtaining a binary image, which can adaptively determine the threshold, and enables the obtained binary image to better show the difference between normal points and defective points of the screen image. It can effectively remove the interference isolated points and improve the display effect of the screen defect points in the screen image. A method for effectively removing interference points on the screen image is provided, and the screen image is denoised, which reduces the computing resources required for recognition and guarantees the recognition effect of subsequent screen defects. It can effectively identify the characteristics of the contour boundary line at the boundary between the normal point and the defect point, so as to realize the contour recognition and positioning of the screen point defect position. Effectively identify the defects of the screen points, and obtain the number and location information of the defect points, which can effectively guide the production staff to improve the screen, enhance the recognition effect, and enrich the recognition content.

FIG. 9 is a schematic structural diagram of a point defect determination device for an OLED screen provided by an embodiment of the present application.

Referring to FIG. 9, the device 900 includes:

The obtaining module 901 is used to obtain an image of the OLED screen.

The conversion module 902 is used to convert the image into a YUV image and extract the Y image corresponding to the YUV image.

The recognition module 903 is used to recognize the contour size of the defect position of the OLED screen point according to the image characteristics of the Y image, and use the contour size as the contour feature.

The judging module 904 is used for judging the defects of the OLED screen points according to the contour characteristics.

Optionally, in some embodiments, referring to FIG. 10, the identification module 903 includes:

The conversion sub-module 9031 is used to convert the Y image into a binary image according to the image characteristics of the Y image;

The processing sub-module 9032 is used to perform morphological processing on the binary image to obtain the target binary image;

The recognition sub-module 9033 is used to recognize the outline size of the defect position of the OLED screen point according to the target binary image, and use the outline size as the outline feature.

Optionally, in some embodiments, the conversion sub-module 9031 is specifically used for:

Traverse each pixel of the Y image to determine the number of pixels with different gray values;

According to the number of pixels with different gray values, a pixel distribution curve is formed;

Determine the pixel gray threshold according to the pixel distribution curve;

Compare the gray value of each pixel with the pixel gray threshold;

According to the result of the comparison, the Y image is converted into a binary image.

Optionally, in some embodiments, the processing sub-module 9032 is specifically configured to:

Use the first-size structural elements to corrode the binary image;

Use the second-size structural element to expand the binary image after the corrosion treatment;

Using the structural elements of the third size to perform corrosion processing on the binary image after the expansion process again to obtain the target binary image, the first size, the second size, and the third size may be the same or different.

Optionally, in some embodiments, the identification sub-module 9033 is specifically used to:

According to the target binary image, determine the outline set of the defect position of the OLED screen point;

Traverse each element of the contour line set, identify the contour line rectangle, and form the contour line rectangle set;

The length and width of each contour rectangle in the contour rectangle set are used as the contour size.

Optionally, in some embodiments, the determination module 904 is specifically configured to:

Keep the contour rectangles whose length and width are greater than the set threshold in the contour rectangle set;

Form a point defect set according to the retained contour rectangles and the coordinate information corresponding to each contour rectangle;

Determine the number of point defects and the location information of each point defect according to the point defect collection.

It should be noted that the explanation of the OLED screen point defect determination method embodiment in the aforementioned embodiments of FIGS. 1 to 8 is also applicable to the OLED screen point defect determination device 900 of this embodiment. The implementation principle is similar, and it is not here. Go into details again.

In this embodiment, the image of the OLED screen is acquired; the image is converted to a YUV image, and the Y image corresponding to the YUV image is extracted; according to the image characteristics of the Y image, the outline size of the defect location of the OLED screen is identified, and the outline size As a contour feature: Defect judgment on OLED screen points based on contour characteristics can improve the efficiency of defect detection of OLED screens, increase detection speed, and improve defect detection effects.

11, the electronic device 1100 of this embodiment includes a housing 1101, a processor 1102, a memory 1103, a circuit board 1104, and a power supply circuit 1105. The circuit board 1104 is arranged inside the space enclosed by the housing 1101, and the processor 1102 And the memory 1103 are arranged on the circuit board 1104; the power supply circuit 1105 is used to supply power to various circuits or devices of the electronic device 1100; the memory 1103 is used to store executable program codes; the processor 1102 reads the executable stored in the memory 1103 Program code to run the program corresponding to the executable program code for execution:

Obtain the image of the OLED screen;

Convert the image to a YUV image, and extract the Y image corresponding to the YUV image;

According to the image characteristics of the Y image, identify the outline size of the defect location of the OLED screen point, and use the outline size as the outline feature;

According to the contour characteristics, the defects of the OLED screen are judged.

It should be noted that the explanation of the embodiment of the OLED screen point defect determination method in the aforementioned embodiments of FIG. 1 to FIG. 8 is also applicable to the electronic device 1100 of this embodiment, and its implementation principles are similar, and will not be repeated here.

In order to implement the foregoing embodiments, the embodiments of the present application propose a non-transitory computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the OLED screen point defect determination method of the foregoing method embodiment is implemented.

It should be noted that in the description of this application, the terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance. In addition, in the description of the present application, unless otherwise specified, "plurality" means two or more.

Any process or method description described in the flowchart or described in other ways herein can be understood as a module, segment, or part of code that includes one or more executable instructions for implementing specific logical functions or steps of the process , And the scope of the preferred embodiments of the present application includes additional implementations, which may not be in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved. This should It is understood by those skilled in the art to which the embodiments of the present application belong.

It should be understood that each part of this application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if it is implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of the following technologies known in the art: Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate array (PGA), field programmable gate array (FPGA), etc.

A person of ordinary skill in the art can understand that all or part of the steps carried in the method of the foregoing embodiments can be implemented by a program instructing relevant hardware to complete. The program can be stored in a computer-readable storage medium. When executed, it includes one of the steps of the method embodiment or a combination thereof.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or software function modules. If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

The aforementioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

In the description of this specification, descriptions with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. mean specific features described in conjunction with the embodiment or example , The structure, materials, or characteristics are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above-mentioned terms do not necessarily refer to the same embodiment or example. Moreover, the described specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

Although the embodiments of the present application have been shown and described above, it can be understood that the above-mentioned embodiments are exemplary and should not be construed as limiting the present application. A person of ordinary skill in the art can comment on the foregoing within the scope of the present application. The embodiment undergoes changes, modifications, substitutions, and modifications.

Claims

A method for determining point defects of an OLED screen, characterized in that the method includes:

Obtain the image of the OLED screen;

Converting the image into a YUV image, and extracting a Y image corresponding to the YUV image;

According to the image feature of the Y image, identify the outline size of the defect position of the OLED screen point, and use the outline size as the outline feature;

Defect judgment is performed on the OLED screen dots according to the contour feature.
The method for determining point defects of an OLED screen according to claim 1, wherein the identifying the outline size of the defect position of the OLED screen according to the image characteristics of the Y image comprises:

Converting the Y image into a binary image according to the image characteristics of the Y image;

Performing morphological processing on the binary image to obtain a target binary image;

According to the target binary image, the outline size of the defect position of the OLED screen point is identified.
The method for determining point defects of an OLED screen according to claim 2, wherein the converting the Y image into a binary image according to the image characteristics of the Y image comprises:

Traverse each pixel of the Y image to determine the number of pixels with different gray values;

Forming a pixel distribution curve diagram according to the number of pixels with different gray values;

Determining a pixel gray level threshold according to the pixel distribution curve;

Comparing the gray value of each pixel with the pixel gray threshold;

According to the result of the comparison, the Y image is converted into a binary image.
The method for determining point defects of an OLED screen according to claim 2 or 3, wherein said performing morphological processing on said binary image to obtain a target binary image comprises:

Corroding the binary image by using structural elements of the first size;

Use the second-size structural element to expand the binary image after the corrosion treatment;

Using the structural elements of the third size to perform corrosion processing on the binary image after expansion processing again to obtain the target binary image, the first size, the second size, and the third size may be the same or different same.
The method for determining point defects of an OLED screen according to any one of claims 2-4, wherein the identifying the outline size of the defect position of the OLED screen according to the target binary image comprises:

According to the target binary image, determine the outline set of the defect position of the OLED screen point;

Traverse each element of the contour line set, identify contour line rectangles, and form a contour line rectangle set;

The length and width of each contour rectangle in the contour rectangle set are used as the contour size.
7. The method for determining point defects of an OLED screen according to claim 5, wherein said determining the point defects of said OLED screen according to said contour feature comprises:

Retaining the contour rectangles whose length and width are both greater than a set threshold in the contour rectangle set;

Forming a point defect set according to the retained outline rectangles and the coordinate information corresponding to each of the outline rectangles;

The number of point defects and the location information of each point defect are determined according to the set of point defects.
An OLED screen point defect judging device, characterized in that the device comprises:

The acquisition module is used to acquire the image of the OLED screen;

A conversion module for converting the image into a YUV image, and extracting a Y image corresponding to the YUV image;

An identification module, configured to identify the outline size of the defect position of the OLED screen point according to the image feature of the Y image, and use the outline size as the outline feature;

The judging module is used for judging the defects of the OLED screen points according to the contour characteristics.
7. The device for determining point defects of an OLED screen according to claim 7, wherein the identification module comprises:

A conversion sub-module for converting the Y image into a binary image according to the image characteristics of the Y image;

The processing sub-module is used to perform morphological processing on the binary image to obtain the target binary image;

The recognition sub-module is used to recognize the outline size of the defect position of the OLED screen point according to the target binary image.
8. The OLED screen point defect judging device according to claim 8, wherein the conversion sub-module is specifically used for:

Traverse each pixel of the Y image to determine the number of pixels with different gray values;

Forming a pixel distribution curve diagram according to the number of pixels with different gray values;

Determining a pixel gray level threshold according to the pixel distribution curve;

Comparing the gray value of each pixel with the pixel gray threshold;

According to the result of the comparison, the Y image is converted into a binary image.
The device for determining point defects of an OLED screen according to claim 8 or 9, wherein the processing sub-module is specifically configured to:

Corroding the binary image by using structural elements of the first size;

Use the second-size structural element to expand the binary image after the corrosion treatment;

Using the structural elements of the third size to perform corrosion processing on the binary image after expansion processing again to obtain the target binary image, the first size, the second size, and the third size may be the same or different same.
The device for determining point defects of an OLED screen according to any one of claims 8-10, wherein the identification sub-module is specifically used for:

According to the target binary image, determine the outline set of the defect position of the OLED screen point;

Traverse each element of the contour line set, identify contour line rectangles, and form a contour line rectangle set;

The length and width of each contour rectangle in the contour rectangle set are used as the contour size.
The OLED screen point defect judging device according to claim 11, wherein the judging module is specifically used for:

Retaining the contour rectangles whose length and width are both greater than a set threshold in the contour rectangle set;

Forming a point defect set according to the retained outline rectangles and the coordinate information corresponding to each of the outline rectangles;

The number of point defects and the location information of each point defect are determined according to the set of point defects.
A non-temporary computer-readable storage medium with a computer program stored thereon, which is characterized in that when the program is executed by a processor, the method for determining a point defect of an OLED screen according to any one of claims 1 to 6 is realized.
An electronic device comprising a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is arranged inside a space enclosed by the housing, the processor and the memory Is arranged on the circuit board; the power supply circuit is used to supply power to various circuits or devices of the electronic equipment; the memory is used to store executable program codes; the processor reads and stores in the memory The executable program code for running the program corresponding to the executable program code is used to execute the method for determining the point defect of the OLED screen according to any one of claims 1-6.