CN113785181A - OLED screen point defect judgment method and device, storage medium and electronic equipment - Google Patents

OLED screen point defect judgment method and device, storage medium and electronic equipment Download PDF

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CN113785181A
CN113785181A CN202080000368.1A CN202080000368A CN113785181A CN 113785181 A CN113785181 A CN 113785181A CN 202080000368 A CN202080000368 A CN 202080000368A CN 113785181 A CN113785181 A CN 113785181A
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image
oled screen
defect
point
size
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王帅
姜立
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BOE Technology Group Co Ltd
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BOE Technology Group Co Ltd
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Abstract

The application provides an OLED screen point defect judgment method, device, storage medium and electronic equipment, wherein the method comprises the steps of obtaining an image of an OLED screen; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; and judging the defects of the OLED screen points according to the profile characteristics. Can promote the defect point detection efficiency of OLED screen through this application, promote detection speed, promote defect point detection effect.

Description

OLED screen point defect judgment method and device, storage medium and electronic equipment Technical Field
The present disclosure relates to the field of electronic devices, and in particular, to a method and an apparatus for determining a dot defect on an OLED screen, a storage medium, and an electronic device.
Background
Defect point detection is an indispensable link in the display screen production and manufacturing process, and the high-efficiency and accurate defect point detection method can detect defective products, improve the shipment quality of the display screen, can save cost and improve enterprise benefits.
The defect point detection method in the related art mainly relies 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 poor.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the application provides an OLED screen point defect judging method, an OLED screen point defect judging device, a storage medium and electronic equipment, which can improve the defect point detection efficiency of an OLED screen, improve the detection speed and improve the defect point detection effect.
In order to achieve the above object, an embodiment of the present application provides a method for determining a dot defect of an OLED screen, including: acquiring an image of an OLED screen; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; and judging the defects of the OLED screen points according to the profile characteristics.
According to the method for judging the point defects of the OLED screen, provided by the embodiment of the first aspect of the application, the image of the OLED screen is obtained; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
In order to achieve the above object, an OLED screen point defect determining apparatus according to an embodiment of the second aspect of the present application includes: the acquisition module is used for acquiring an image of the OLED screen; the conversion module is used for converting the image into a YUV image and extracting a Y image corresponding to the YUV image; the identification module is used for identifying the outline size of the defect position of the OLED screen point according to the image characteristics of the Y image and taking the outline size as the outline characteristic; and the judging module is used for judging the defects of the OLED screen points according to the contour features.
The device for judging the point defect of the OLED screen provided by the embodiment of the second aspect of the application acquires an 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 characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
A non-transitory computer-readable storage medium is provided in an embodiment of the third aspect of the present application, and when executed by a processor of an electronic device, enables the electronic device to perform an OLED screen point defect determination method, the method including: the embodiment of the first aspect of the application provides an OLED screen point defect judgment method.
The non-transitory computer readable storage medium provided in the third embodiment of the present application, includes acquiring an image of an OLED screen; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
An embodiment of a fourth aspect of the present application provides an electronic device, including: the device comprises a shell, a processor, a memory, a circuit board and a power circuit, wherein the circuit board is arranged in a space enclosed by the shell, and the processor and the memory are arranged on the circuit board; the power supply circuit is used for supplying power to each circuit or device of the electronic equipment; the memory is used for storing executable program codes; the processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to execute the method for determining the point defect of the OLED screen provided by the embodiment of the first aspect of the present application.
According to the electronic device provided by the embodiment of the fourth aspect of the application, the image of the OLED screen is acquired; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flowchart illustrating a method for determining a point defect on an OLED screen according to an embodiment of the present application;
FIG. 2 is a schematic image diagram of an OLED screen according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a Y image in an embodiment of the present application;
FIG. 4 is a schematic flowchart illustrating a method for determining a point defect on an OLED screen according to another embodiment of the present disclosure;
FIG. 5 is a diagram illustrating a pixel distribution graph according to an embodiment of the present disclosure;
FIG. 6 is a schematic diagram illustrating a Y image converted into a binary image according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a target binary image according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a point defect of an OLED screen according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an OLED screen point defect determining apparatus according to an embodiment of the present application;
FIG. 10 is a schematic structural diagram of an OLED screen point defect determining apparatus according to another embodiment of the present application;
fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application. On the contrary, the embodiments of the application include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Fig. 1 is a schematic flowchart of a method for determining a point defect on an OLED screen according to an embodiment of the present application.
The present embodiment is exemplified in that the OLED screen point defect determination method is configured as an OLED screen point defect determination device.
Among them, an OLED screen, i.e., an Organic Light-Emitting semiconductor (OLED) screen.
The method for determining the point defect of the OLED screen in this embodiment may be configured in an apparatus for determining the point defect of the OLED screen, and the apparatus for determining the point defect of the OLED screen may be disposed in a server, or may also be disposed in an electronic device, which is not limited in this embodiment.
The present embodiment takes the OLED screen point defect determination method as an example configured in an electronic device.
It should be noted that the execution main body in the embodiment of the present application may be, for example, a Central Processing Unit (CPU) in a server or an electronic device in terms of hardware, and may be, for example, a related background service in the server or the electronic device in terms of software, which is not limited to this.
Referring to fig. 1, the method includes:
s101: an image of the OLED screen is acquired.
Because the difference of the display brightness of the defective points of the screen is considered, a bright and dark outline boundary line can be formed at the boundary of the normal points and the defective points of the screen, and the difference of the display brightness can be reflected in the image of the screen, therefore, the embodiment of the application can judge the defects of the screen points by using the image of the OLED screen, can effectively use the image characteristics of the defective points of the screen, and enables the judgment result to be accurate.
When the image of the OLED screen is obtained, the device with an image capture function (such as a mobile terminal, a camera, etc.) may capture a screen display picture and use the screen display picture as the image of the screen, which is not limited.
Referring to fig. 2, fig. 2 is a schematic image diagram of an OLED screen according to an embodiment of the present application, where the schematic image includes a plurality of screen points, and whether each screen point is a defective point is determined by using the OLED screen point defect determining method in the embodiment of the present application, and when the screen point is determined as a defective point, the position information of the defective point may be determined, and the number of screen defective points is counted.
The above-mentioned image of the OLED screen is acquired, and may be denoted as I1, and when I1 is acquired, I1 may be input to the electronic device of the OLED screen point defect determination method executed, and the defect determination of the screen point is automatically performed by the electronic device.
The image of the OLED screen may be a RAW image obtained by shooting, and the RAW image may be, for example, an unprocessed RAW format image acquired by an image sensor of an electronic device, which is not limited in this respect.
The RAW format image is an original image obtained by converting a captured light source signal into a digital signal by an image sensor.
S102: and converting the image into a YUV image, and extracting a Y image corresponding to the YUV image.
S103: and identifying the outline size of the defect position of the OLED screen point according to the image characteristics of the Y image, and taking the outline size as the outline characteristic.
In some embodiments, the image feature may be, for example, a brightness, a gray scale, a chromaticity, a saturation, and the like of the image, so that the defect point in the screen point may be identified by combining the corresponding brightness, gray scale, chromaticity, saturation, and the like, or may be identified by combining any other possible image features, which is not limited in this respect.
In the embodiment of the application, when the outline characteristics of the defect position of the OLED screen point are identified according to the image characteristics of the image, the image can be converted into a YUV image, a Y image corresponding to the YUV image is extracted, the outline characteristics of the defect position of the OLED screen point are identified according to the image characteristics of the Y image, the OLED screen defect point can be effectively identified in a follow-up mode by extracting the gray level image of the OLED screen, and the identification accuracy of the screen defect point is improved.
Referring to fig. 3, fig. 3 is a schematic diagram of a Y image in the embodiment of the present application.
The YUV image refers to an image that can be processed by a display of an electronic device and has a YUV format.
Where the luminance signal of an image is called Y and the chrominance signal is composed of two separate signals, often called U and V, depending on the color system and format. In this case, after the Image of the OLED screen is obtained, the Image may be converted into a YUV Image by an Image Signal Processing (ISP), a Y Image corresponding to the YUV Image is extracted, and the outline feature of the defect position of the OLED screen point is recognized from the Image feature of the Y Image.
S104: and judging the defects of the OLED screen points according to the profile characteristics.
After the outline characteristic of the defect position of the OLED screen point is identified, the outline characteristic may be compared with a set characteristic threshold, and when a result of comparing the outline characteristic with the set characteristic threshold satisfies a condition, the screen point of the defect position corresponding to the outline characteristic is determined to be a defect point, and position information of the defect point is recorded, which is not limited herein.
In the embodiment, an image of an OLED screen is acquired; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
Fig. 4 is a schematic flowchart of a method for determining a point defect on an OLED screen according to another embodiment of the present application.
Referring to fig. 4, the method includes:
in the description of the present embodiment, reference may be made to fig. 2 and fig. 3 together.
Referring to fig. 4, the method includes:
s401: an image of the OLED screen is acquired.
Because the difference of the display brightness of the defective points of the screen is considered, a bright and dark outline boundary line can be formed at the boundary of the normal points and the defective points of the screen, and the difference of the display brightness can be reflected in the image of the screen, therefore, the embodiment of the application can judge the defects of the screen points by using the image of the OLED screen, can effectively use the image characteristics of the defective points of the screen, and enables the judgment result to be accurate.
When the image of the OLED screen is obtained, the device with an image capture function (such as a mobile terminal, a camera, etc.) may capture a screen display picture and use the screen display picture as the image of the screen, which is not limited.
Referring to fig. 2, fig. 2 is a schematic image diagram of an OLED screen according to an embodiment of the present application, where the schematic image includes a plurality of screen points, and whether each screen point is a defective point is determined by using the OLED screen point defect determining method in the embodiment of the present application, and when the screen point is determined as a defective point, the position information of the defective point may be determined, and the number of screen defective points is counted.
The above-mentioned image of the OLED screen is acquired, and may be denoted as I1, and when I1 is acquired, I1 may be input to the electronic device of the OLED screen point defect determination method executed, and the defect determination of the screen point is automatically performed by the electronic device.
The image of the OLED screen may be a RAW image obtained by shooting, and the RAW image may be, for example, an unprocessed RAW format image acquired by an image sensor of an electronic device, which is not limited in this respect.
The RAW format image is an original image obtained by converting a captured light source signal into a digital signal by an image sensor.
S402: and converting the image into a YUV image, and extracting a Y image corresponding to the YUV image.
The YUV image refers to an image that can be processed by a display of an electronic device and has a YUV format.
Where the luminance signal of an image is called Y and the chrominance signal is composed of two separate signals, often called U and V, depending on the color system and format. In this case, after the Image of the OLED screen is obtained, the Image may be converted into a YUV Image by an Image Signal Processing (ISP), a Y Image corresponding to the YUV Image is extracted, and the outline feature of the defect position of the OLED screen point is recognized from the Image feature of the Y Image.
S403: and converting the Y image into a binary image according to the image characteristics of the Y image.
Optionally, the Y image is converted into a binary image according to the image characteristics of the Y image, which may be traversing each pixel point of the Y image, determining the number of pixel points with different gray values, forming a pixel distribution graph according to the number of pixel points with different gray values, determining a pixel gray threshold according to the pixel distribution graph, comparing the gray value of each pixel point with the pixel gray threshold, and converting the Y image into a binary image according to the comparison result.
The Binary Image (Binary Image) refers to that each pixel on the Image has only two possible values or grayscale states, and usually, a black-and-white, B & W, and monochrome Image is used to represent the Binary Image, and the Image binarization is used to facilitate extracting information in the Image, so that the recognition efficiency of the Binary Image can be increased when computer recognition is performed.
Referring to fig. 5 and fig. 6, fig. 5 is a schematic diagram of a pixel distribution graph according to an embodiment of the present application, where I3 denotes the pixel distribution graph, and fig. 6 is a schematic diagram of a Y image converted into a binary image according to an embodiment of the present application.
As an example, traversing each pixel point in the Y image I2, counting the number of pixel points corresponding to different gray values in the Y image I2 to obtain a pixel distribution graph I3, wherein the number of the defective points is different from the number of the normal pixel points by an order of magnitude, so that the defective points should be located at extreme values of the curve, and a pixel gray threshold may be calculated according to the pixel distribution graph I3, so as to traverse all the pixel points of the image with the pixel gray threshold as a determination condition, set the gray level of the pixel point with the gray value lower than the pixel gray threshold to 255 (full white), and set the gray level of the pixel point with the gray value higher than the pixel gray threshold to 0 (full black), thereby forming a binary image I4.
The method for obtaining the binary image conveniently and quickly is provided, the threshold value can be determined in a self-adaptive mode, and the obtained binary image can well show the difference between the normal point and the defect point of the screen image.
S404: and carrying out morphological processing on the binary image to obtain a target binary image.
Optionally, the binary image is subjected to morphological processing to obtain a target binary image, the binary image may be subjected to erosion processing by using a structural element with a first size, the binary image after the erosion processing is subjected to expansion processing by using a structural element with a second size, and the binary image after the expansion processing is subjected to erosion processing again by using a structural element with a third size to obtain the target binary image, where the first size, the second size, and the third size may be the same or different.
The first dimension a1 a1, the second dimension a2 a2, and the third dimension a3 a3 may be adjusted according to the size and resolution of the image capturing device and the panel, and generally, the value ranges of a1, a2, and a3 are [3,7], and in the present embodiment, a1 is 5, a2 is 3, and a3 is 3, which is not limited.
The target binary image may be represented as I5, see fig. 7, where fig. 7 is a schematic diagram of the target binary image according to the embodiment of the present application.
The method for effectively removing the interference points of the screen image is provided, the denoising processing is carried out on the screen image, the calculation resources required to be consumed for recognition are reduced, and the recognition effect of the subsequent screen defect points is guaranteed.
S405: and identifying the outline size of the defect position of the OLED screen point according to the target binary image, and taking the outline size as an outline characteristic.
Optionally, the contour size of the defect position of the OLED screen point is identified according to the target binary image, which may be determining a contour line set of the defect position of the OLED screen point according to the target binary image, traversing each element of the contour line set, identifying a contour line rectangle, forming a contour line rectangle set, and taking the length and width of each contour line rectangle in the contour line rectangle set as the contour size, so as to effectively identify the feature of the contour boundary line at the boundary between the normal point and the defect point, and realize the contour identification and positioning of the defect position of the screen point.
S406: and reserving contour line rectangles with the length and width larger than a set threshold value in the contour line rectangle set.
S407: and forming a point defect set according to the reserved contour line rectangles and the coordinate information corresponding to each contour line rectangle.
As an example, a set of contour lines of the defect positions of the OLED screen point may be determined according to the target binary image I5, and the screen point corresponding to the defect position may be a suspected defect point, so that the set of contour lines may be regarded as a set of contour lines of the suspected points, and then, each element in the set of contour lines may be traversed to determine a contour line rectangle therefrom to form a set of contour line rectangles, and whether the corresponding screen point is a defect point is determined according to the length and width of each contour line rectangle in the set of contour line rectangles.
Optionally, whether the corresponding screen point is a defect point is determined according to the length and the width of each contour line rectangle in the contour line rectangle set, where if both the length and the width are less than a4, the contour line rectangle is deleted from the contour line rectangle set, otherwise, the contour line rectangle set after traversal is retained, and a point defect set is formed according to the retained contour line rectangle and the coordinate information corresponding to each contour line rectangle.
It should be noted that the size of the a4 may be adjusted according to the size and resolution of the image capture device and the panel, and for this embodiment, the a4 is 4, which is not limited.
S408: and determining the number of point defects and the position information of each point defect according to the point defect set.
After the point defect set is obtained, the number of the point defects in the point defect set and the position information of the point defects can be counted, so that the point defect judgment of the OLED screen is completed.
Referring to fig. 8, fig. 8 is a schematic diagram of a point defect of an OLED screen in an embodiment of the present application. Fig. 8 is an output result of a design algorithm based on the flowchart shown in fig. 4, and the purpose of determining the number and positions of the dot defects of the OLED screen can be achieved by the method, so that the problem that a large number of dot defects cannot be quantitatively described is solved, technical support is provided for the bad judgment of large-size printed OLED display screens, the defects of the screen dots are effectively identified, the number and position information of the defective dots are obtained, production personnel can be effectively guided to improve the screen, the identification effect is improved, and the identification content is enriched.
In the embodiment, an image of an OLED screen is acquired; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved. The method for conveniently and quickly obtaining the binary image can adaptively determine the threshold value and enable the obtained binary image to better show the difference between the normal point and the defect point of the screen image. The method can effectively remove the interference isolated points and improve the display effect of the screen defect points in the screen image. The method for effectively removing the screen image interference points is provided, the screen image is subjected to denoising processing, the calculation resources required to be consumed for identification are reduced, and the identification effect of the subsequent screen defect points is guaranteed. The method can effectively identify the characteristics of the outline boundary at the boundary of the normal point and the defect point, thereby realizing the outline identification and positioning of the defect position of the screen point. The defects of the screen points are effectively identified, the number and the position information of the defect points are obtained, production personnel can be effectively guided to improve the screen, the identification effect is improved, and the identification content is enriched.
Fig. 9 is a schematic structural diagram of an OLED screen point defect determining device according to an embodiment of the present application.
Referring to fig. 9, the apparatus 900 includes:
an acquiring module 901, configured to acquire an image of an OLED screen.
A converting module 902, configured to convert the image into a YUV image, and extract a Y image corresponding to the YUV image.
And the identifying module 903 is used for identifying the outline size of the defect position of the OLED screen point according to the image characteristics of the Y image, and taking the outline size as the outline characteristic.
And 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 identifying module 903 includes:
the conversion sub-module 9031 is configured to convert the Y image into a binary image according to an image feature of the Y image;
the processing submodule 9032 is configured to perform morphological processing on the binary image to obtain a target binary image;
and the identifying sub-module 9033 is configured to identify the contour size of the defect position of the OLED screen point according to the target binary image, and use the contour size as a contour feature.
Optionally, in some embodiments, the conversion sub-module 9031 is specifically configured to:
traversing each pixel point of the Y image, and determining the number of the pixel points with different gray values;
forming a pixel distribution curve graph according to the number of the pixel points with different gray values;
determining a pixel gray threshold according to the pixel distribution curve graph;
comparing the gray value of each pixel point with a pixel gray threshold value;
and converting the Y image into a binary image according to the comparison result.
Optionally, in some embodiments, the processing sub-module 9032 is specifically configured to:
carrying out corrosion treatment on the binary image by adopting structural elements with a first size;
performing expansion processing on the corroded binary image by using structural elements with a second size;
and carrying out corrosion treatment on the expanded binary image again by adopting the structural element with the third size to obtain a target binary image, wherein the first size, the second size and the third size can be the same or different.
Optionally, in some embodiments, the identifying sub-module 9033 is specifically configured to:
determining a contour line set of the defect positions of the OLED screen points according to the target binary image;
traversing each element of the contour line set, identifying a contour line rectangle, and forming a contour line rectangle set;
and taking the length and the width of each contour rectangle in the contour rectangle set as contour dimensions.
Optionally, in some embodiments, the determining module 904 is specifically configured to:
reserving contour line rectangles with the length and width larger than a set threshold value in the contour line rectangle set;
forming a point defect set according to the reserved contour line rectangles and the coordinate information corresponding to each contour line rectangle;
and determining the number of point defects and the position information of each point defect according to the point defect set.
It should be noted that the explanation of the OLED screen point defect determination method in the foregoing embodiments of fig. 1 to 8 is also applicable to the OLED screen point defect determination apparatus 900 in this embodiment, and the implementation principle thereof is similar and is not repeated here.
In the embodiment, an image of an OLED screen is acquired; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Referring to fig. 11, an electronic device 1100 of the present embodiment includes a housing 1101, a processor 1102, a memory 1103, a circuit board 1104 and a power circuit 1105, where the circuit board 1104 is disposed inside a space surrounded by the housing 1101, and the processor 1102 and the memory 1103 are disposed on the circuit board 1104; a power supply circuit 1105 for supplying power to various circuits or devices of the electronic apparatus 1100; the memory 1103 is used to store executable program code; the processor 1102 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 1103, for performing:
acquiring an image of an OLED screen;
converting the image into a YUV image, and extracting a Y image corresponding to the YUV image;
according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic;
and judging the defects of the OLED screen points according to the profile characteristics.
It should be noted that the explanation of the OLED screen point defect determination method in the foregoing embodiments of fig. 1 to fig. 8 is also applicable to the electronic device 1100 in this embodiment, and the implementation principle is similar, and is not repeated here.
In the embodiment, an image of an OLED screen is acquired; converting the image into a YUV image, and extracting a Y image corresponding to the YUV image; according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic; according to the method, the defect judgment is carried out on the OLED screen points according to the profile characteristics, the defect point detection efficiency of the OLED screen can be improved, the detection speed is improved, and the defect point detection effect is improved.
In order to implement the foregoing embodiments, the present application provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for determining the OLED screen point defect of the foregoing method embodiments is implemented.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present application, "a plurality" means two or more unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include 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 other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (14)

  1. An OLED screen point defect judgment method is characterized by comprising the following steps:
    acquiring an image of an OLED screen;
    converting the image into a YUV image, and extracting a Y image corresponding to the YUV image;
    according to the image characteristics of the Y image, identifying the outline size of the defect position of the OLED screen point, and taking the outline size as the outline characteristic;
    and judging the defects of the OLED screen points according to the profile characteristics.
  2. The method for determining the defect of the OLED screen point as claimed in claim 1, wherein the step of identifying the outline size of the defect position of the OLED screen point according to the image feature of the Y image comprises the following steps:
    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;
    and identifying the outline size of the defect position of the OLED screen point according to the target binary image.
  3. The OLED screen point defect determining method of claim 2, wherein the converting the Y image into a binary image according to the image characteristics of the Y image comprises:
    traversing each pixel point of the Y image, and determining the number of the pixel points with different gray values;
    forming a pixel distribution curve graph according to the number of the pixel points with different gray values;
    determining a pixel gray threshold according to the pixel distribution curve graph;
    comparing the gray value of each pixel point with the pixel gray threshold value;
    and converting the Y image into a binary image according to the comparison result.
  4. The method for determining the point defect on the OLED screen according to claim 2 or 3, wherein the morphological processing of the binary image to obtain the target binary image comprises:
    carrying out corrosion treatment on the binary image by adopting structural elements with a first size;
    performing expansion processing on the corroded binary image by using structural elements with a second size;
    and corroding the expanded binary image again by adopting structural elements with a third size to obtain the target binary image, wherein the first size, the second size and the third size can be the same or different.
  5. The OLED screen point defect judging method of any one of claims 2 to 4, wherein the identifying the outline size of the defect position of the OLED screen point according to the target binary image comprises:
    determining a contour line set of the defect positions of the OLED screen points according to the target binary image;
    traversing each element of the contour line set, identifying a contour line rectangle, and forming a contour line rectangle set;
    and taking the length and the width of each contour rectangle in the contour rectangle set as the contour size.
  6. The OLED screen point defect judging method of claim 5, wherein the defect judgment of the OLED screen point according to the contour feature comprises:
    reserving contour line rectangles with the length and the width larger than a set threshold value in the contour line rectangle set;
    forming a point defect set according to the reserved contour line rectangles and the coordinate information corresponding to each contour line rectangle;
    and determining the number of point defects and the position information of each point defect according to the point defect set.
  7. An OLED screen point defect judging device, characterized in that, the device includes:
    the acquisition module is used for acquiring an image of the OLED screen;
    the conversion module is used for converting the image into a YUV image and extracting a Y image corresponding to the YUV image;
    the identification module is used for identifying the outline size of the defect position of the OLED screen point according to the image characteristics of the Y image and taking the outline size as the outline characteristic;
    and the judging module is used for judging the defects of the OLED screen points according to the contour features.
  8. The OLED screen point defect determining apparatus of claim 7, wherein the identifying module includes:
    the conversion sub-module is used for converting the Y image into a binary image according to the image characteristics of the Y image;
    the processing submodule is used for carrying out morphological processing on the binary image to obtain a target binary image;
    and the identification submodule is used for identifying the outline size of the defect position of the OLED screen point according to the target binary image.
  9. The OLED screen point defect determining apparatus of claim 8, wherein the converting submodule is specifically configured to:
    traversing each pixel point of the Y image, and determining the number of the pixel points with different gray values;
    forming a pixel distribution curve graph according to the number of the pixel points with different gray values;
    determining a pixel gray threshold according to the pixel distribution curve graph;
    comparing the gray value of each pixel point with the pixel gray threshold value;
    and converting the Y image into a binary image according to the comparison result.
  10. The OLED screen point defect determining apparatus of claim 8 or 9, wherein the processing submodule is specifically configured to:
    carrying out corrosion treatment on the binary image by adopting structural elements with a first size;
    performing expansion processing on the corroded binary image by using structural elements with a second size;
    and carrying out corrosion treatment on the expanded binary image again by adopting structural elements with a third size to obtain the target binary image, wherein the first size, the second size and the third size can be the same or different.
  11. The OLED screen point defect determining apparatus of any one of claims 8-10, wherein the identification submodule is specifically configured to:
    determining a contour line set of the defect positions of the OLED screen points according to the target binary image;
    traversing each element of the contour line set, identifying a contour line rectangle, and forming a contour line rectangle set;
    and taking the length and the width of each contour rectangle in the contour rectangle set as the contour size.
  12. The OLED screen point defect determining device of claim 11, wherein the determining module is specifically configured to:
    reserving contour line rectangles with the length and the width larger than a set threshold value in the contour line rectangle set;
    forming a point defect set according to the reserved contour line rectangles and the coordinate information corresponding to each contour line rectangle;
    and determining the number of point defects and the position information of each point defect according to the point defect set.
  13. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the OLED screen point defect determining method according to any one of claims 1 to 6.
  14. An electronic device comprising a housing, a processor, a memory, a circuit board, and a power circuit, wherein the circuit board is disposed inside a space enclosed by the housing, the processor and the memory being disposed on the circuit board; the power supply circuit is used for supplying power to each circuit or device of the electronic equipment; the memory is used for storing executable program codes; the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory for performing the OLED screen point defect determining method according to any one of claims 1 to 6.
CN202080000368.1A 2020-03-24 2020-03-24 OLED screen point defect judgment method and device, storage medium and electronic equipment Pending CN113785181A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114264669A (en) * 2022-03-03 2022-04-01 武汉精立电子技术有限公司 Screen damage defect detection method, device and equipment and readable storage medium

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117115157B (en) * 2023-10-23 2024-02-06 湖南隆深氢能科技有限公司 Defect detection method, system, terminal equipment and medium based on PEM (PEM) electrolytic cell
CN117237336B (en) * 2023-11-10 2024-02-23 湖南科技大学 Metallized ceramic ring defect detection method, system and readable storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130017402A (en) * 2011-08-10 2013-02-20 주식회사 포스코 Apparatus and method for detecting surface defects of hot billet
CN106204614A (en) * 2016-07-21 2016-12-07 湘潭大学 A kind of workpiece appearance defects detection method based on machine vision
CN107678192A (en) * 2017-07-16 2018-02-09 中科院成都信息技术股份有限公司 A kind of Mura defects detection method and system based on machine vision
US20180190170A1 (en) * 2016-12-29 2018-07-05 Lg Display Co., Ltd. Inspection apparatus and inspection method using the same
CN110895806A (en) * 2019-07-25 2020-03-20 研祥智能科技股份有限公司 Method and system for detecting screen display defects

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004239733A (en) * 2003-02-05 2004-08-26 Seiko Epson Corp Defect detection method and apparatus of screen
CN105301810A (en) * 2015-11-24 2016-02-03 上海斐讯数据通信技术有限公司 Screen defect detecting method and screen defect detecting device
CN108986069A (en) * 2018-05-30 2018-12-11 哈尔滨工业大学深圳研究生院 A kind of AMOLED display screen defect inspection method, system and storage medium
CN109752394B (en) * 2019-01-28 2021-10-29 凌云光技术股份有限公司 High-precision detection method and system for defects of display screen
CN109886952B (en) * 2019-02-25 2021-04-23 京东方科技集团股份有限公司 Screen defect point detection method and device and computer readable medium
CN110175997B (en) * 2019-05-30 2021-08-06 深圳市洲明科技股份有限公司 Display screen dead pixel detection method and device, computer equipment and storage medium

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130017402A (en) * 2011-08-10 2013-02-20 주식회사 포스코 Apparatus and method for detecting surface defects of hot billet
CN106204614A (en) * 2016-07-21 2016-12-07 湘潭大学 A kind of workpiece appearance defects detection method based on machine vision
US20180190170A1 (en) * 2016-12-29 2018-07-05 Lg Display Co., Ltd. Inspection apparatus and inspection method using the same
CN107678192A (en) * 2017-07-16 2018-02-09 中科院成都信息技术股份有限公司 A kind of Mura defects detection method and system based on machine vision
CN110895806A (en) * 2019-07-25 2020-03-20 研祥智能科技股份有限公司 Method and system for detecting screen display defects

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114264669A (en) * 2022-03-03 2022-04-01 武汉精立电子技术有限公司 Screen damage defect detection method, device and equipment and readable storage medium
CN114264669B (en) * 2022-03-03 2022-05-17 武汉精立电子技术有限公司 Screen damage defect detection method, device and equipment and readable storage medium

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