CN114529497A - Method, system, storage medium, and computer device for detecting aged screen - Google Patents

Method, system, storage medium, and computer device for detecting aged screen Download PDF

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CN114529497A
CN114529497A CN202011318928.6A CN202011318928A CN114529497A CN 114529497 A CN114529497 A CN 114529497A CN 202011318928 A CN202011318928 A CN 202011318928A CN 114529497 A CN114529497 A CN 114529497A
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screen
region
video image
aged
interest
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林楚然
王福泉
徐志克
袁振华
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Beijing Anyun Century Technology Co Ltd
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    • G06T7/0004—Industrial image inspection
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    • G06T2207/10—Image acquisition modality
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T2207/30—Subject of image; Context of image processing
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    • G06T2207/30121—CRT, LCD or plasma display

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Abstract

The invention is applicable to the technical field of computer processing, and provides a method, a system, a storage medium and computer equipment for detecting an aged screen, wherein the method for detecting the aged screen comprises the following steps: monitoring and collecting the video image of the screen; setting a region corresponding to the screen in the video image as a region of interest; and carrying out aging detection on the region of interest in the video image to obtain an aging detection result. Therefore, the invention can reduce manual intervention and improve the detection accuracy and data reliability.

Description

Method, system, storage medium, and computer device for detecting aged screen
Technical Field
The invention relates to the technical field of computer processing, in particular to a method and a system for detecting an aged screen, a storage medium and computer equipment.
Background
In the prior art, a screen aging test needs to use an uncertain video source under a specific environmental condition to perform long-time test work. Wherein the environmental temperature exceeds 40 ℃, and the test duration exceeds 1 month. In a severe environment of a screen aging test, people look at aging conditions on the spot and are easy to cause discomfort and even heatstroke; the aging condition is manually checked at regular intervals by ultra-long test time and large-scale test equipment, and a large amount of manpower and time are consumed; meanwhile, the aging condition is artificially checked, so that the missing inspection is easily caused, and the statistical data lack reliability.
In view of the above, the prior art obviously has inconvenience and defects in practical use, so it is necessary to improve the prior art.
Disclosure of Invention
In view of the above-mentioned drawbacks, the present invention provides a method, a system, a storage medium, and a computer device for detecting an aged screen, which can reduce manual intervention and improve detection accuracy and data reliability.
In order to achieve the above object, the present invention provides a method for detecting an aged screen, comprising:
monitoring and collecting the video image of the screen;
setting a region corresponding to the screen in the video image as a region of interest;
and carrying out aging detection on the region of interest in the video image to obtain an aging detection result.
According to the method for detecting the aged screen, the step of obtaining the aged detection result further comprises the following steps:
and analyzing the aging detection result, and sending alarm information if the aging detection result indicates that the screen has an aging phenomenon.
According to the method for detecting the aged screen, the step of obtaining the aged detection result further comprises the following steps:
and storing the aging detection result and the video image corresponding to the aging detection result.
According to the detection method of the aged screen, when the video image contains a plurality of screens, setting an area containing the plurality of screens in the video image as the region of interest;
the step of detecting aging of the region of interest in the video image comprises:
performing image segmentation on the region of interest in the video image, wherein the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen;
the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises:
and respectively carrying out aging detection on each target area to obtain an aging detection result of the screen corresponding to each target area.
According to the aged screen detection method, the video image is analyzed through a first KNN classifier, a foreground image of the video image is identified, the foreground image is an area corresponding to the screen, and the foreground image is set as the interested area.
According to the detection method of the aged screen, the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises the following steps:
and establishing a second KNN classifier, analyzing the interested region in the video image through the second KNN classifier, and detecting whether the interested region is a black screen image.
According to the detection method of the aged screen, the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises the following steps:
establishing a third KNN classifier, analyzing the interested region in the video image through the third KNN classifier, and detecting whether the interested region is a screen image.
In order to achieve the above object, the present invention also provides a system for detecting an aged screen, comprising:
the image acquisition module is used for monitoring and acquiring the video image of the screen;
the area selection module is used for setting an area corresponding to the screen in the video image as an area of interest;
and the aging detection module is used for carrying out aging detection on the region of interest in the video image to obtain an aging detection result.
In order to achieve the above object, the present invention also provides a storage medium storing a computer program for executing any one of the above-described aged screen detection methods.
In order to achieve the above object, the present invention further provides a computer device including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, the processor implementing the method for detecting an aged screen according to any one of the above items when executing the computer program.
According to the invention, by monitoring and collecting the video image of the screen, the area corresponding to the screen in the video image is set as the region of interest; and carrying out aging detection on the region of interest in the video image to obtain an aging detection result. Through the analysis of the video image containing the screen, the process of screen aging is manually detected and converted into a process which can be processed by a computer, so that manual intervention is reduced, the screen aging phenomenon is automatically identified, and the detection accuracy and the data reliability are improved.
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FIG. 1 is a schematic diagram of a system for detecting aged screens in accordance with one embodiment of the present invention;
FIG. 2 is a schematic diagram of a system for detecting aged screens in accordance with one embodiment of the present invention;
FIG. 3 is a flow chart of a method of detecting an aged screen according to one embodiment of the invention;
fig. 4 is a schematic structural diagram of a computer device provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that references in the specification to "one embodiment," "an example embodiment," etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not intended to refer to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
Moreover, where certain terms are used throughout the description and following claims to refer to particular components or features, those skilled in the art will understand that manufacturers may refer to a component or feature by different names or terms. This specification and the claims that follow do not intend to distinguish between components or features that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. In addition, the term "connected" as used herein includes any direct and indirect electrical connection. Indirect electrical connection means include connection by other means.
Referring to fig. 1 to 2, in a first embodiment of the present invention, there is provided an aged screen detection system 100 including:
the image acquisition module 10 is used for monitoring and acquiring the video image of the screen;
a region selection module 20, configured to set a region corresponding to the screen in the video image as a region of interest;
and the aging detection module 30 is configured to perform aging detection on the region of interest in the video image to obtain an aging detection result.
In this embodiment, the system 100 is complete and very easy to access, and the system 100 for performing aging detection on the screen and obtaining the detection result can be implemented through video analysis based on a smart cloud, and the screen can be a display screen, such as a computer screen, a television screen, and the like. The system 100 includes an image acquisition module 10, a region selection module 20, and a degradation detection module 30. The video image of the screen is monitored and collected by the image acquisition module 10, and the video image is a video frame of a video obtained by monitoring the screen by a monitoring device. Acquire through image acquisition module 10 and contain the video image of screen, it is right in the environment of high temperature to avoid using the manpower the screen is monitored, can also detect with the manual work the ageing process of screen turns into the process that computing equipment can handle, and computing equipment is through right video image handles and analysis and determination whether ageing phenomenon appears in the screen, when ageing phenomenon of screen refers to the broadcast video source, phenomenon such as black screen, flower screen or fixed screen appears in the screen, and it is right to can be through supervisory equipment such as camera the screen monitor the screen. The computing device comprises a region selection module 20 and an aging detection module 30, the region selection module 20 is preferably arranged at the center of the edge calculation, and the region selection module 20 sets the region corresponding to the screen in the video image as a region of interest (ROI), so that the region corresponding to the screen in the video image can be detected and analyzed, and the detection result is more accurate. The aging detection module 30 is preferably disposed in the edge calculation center, and the aging detection module 30 performs aging detection on the region of interest in the video image and determines whether the screen is aged, so as to obtain a detection result. Thus, human intervention can be reduced, and obtaining detection results by the computing device can improve accuracy and data reliability of detection relative to manual detection.
In a second embodiment of the present invention, further comprising:
and the warning module 40 is used for analyzing the aging detection result and sending warning information if the aging detection result indicates that the screen has an aging phenomenon.
In this embodiment, the warning module 40 may be disposed in the smart cloud platform, the warning module 40 receives the aging detection result sent by the aging detection module 30, and when the aging detection result indicates that the screen is aged, sends a warning message to the user to remind the user to check the screen.
In a third embodiment of the present invention, further comprising:
and the storage module 50 is configured to store the aging detection result and the video image corresponding to the aging detection result.
In this embodiment, the storage module 50 is disposed in an intelligent cloud platform, the intelligent cloud platform may push the aging detection result and the video image corresponding to the aging detection result to a user, the user may browse through an intelligent device (a mobile phone or a tablet), and the user may manually check whether the aging detection result is correct according to a requirement. The user can also browse in real time through the browser.
In the fourth embodiment of the present invention, when the video image contains a plurality of the screens, an area containing the plurality of the screens in the video image is set as the region of interest; the system 100 further comprises:
an image segmentation module 60, configured to perform image segmentation on the region of interest in the video image, where the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen;
the degradation detection module 30 includes:
the first detection submodule 31 is configured to perform aging detection on each target area, and obtain an aging detection result of the screen corresponding to each target area.
In this embodiment, the system 100 can perform aging detection on a plurality of screens at the same time, thereby improving efficiency. The plurality of screens are monitored simultaneously by the monitoring camera, and the image acquisition module 10 acquires video images containing the plurality of screens. The region selection module 20 sets a region of the video image including a plurality of the screens as the region of interest. Since the interested region includes a plurality of screens, the interested region is subjected to image segmentation by the image segmentation module 60 and is segmented into a plurality of target regions, each target region corresponds to each screen, and the first detection sub-module 31 can lock each target region to perform aging detection, so as to implement independent analysis on each screen and obtain the aging detection result of the screen corresponding to each target region. The image segmentation module 60 preferably uses a statistical-based analysis method to search for local minima by fitting a polynomial to perform image segmentation, and segments the region corresponding to each screen in the region of interest into independent objects. Of course, image segmentation can also be achieved using prior art image segmentation methods.
In a fifth embodiment of the present invention, the region selection module 20 establishes a first KNN classifier, analyzes the video image through the first KNN classifier, identifies a foreground image of the video image, where the foreground image is a region corresponding to the screen, and sets the foreground image as the region of interest.
In this embodiment, through statistical analysis of consecutive video images, a first KNN (K-nearest neighbor algorithm) classifier is used to automatically identify a region corresponding to the screen in the video images as a foreground image and set the foreground image as the region of interest, thereby locking the screen as an analysis target.
In the sixth embodiment of the present invention, the degradation detection module 30 includes:
and the second detection submodule 32 is configured to establish a second KNN classifier, analyze the region of interest in the video image through the second KNN classifier, and detect whether the region of interest is a black screen image.
In this embodiment, a black screen image dataset of a screen may be trained as training data of the second KNN classifier, and the region of interest in the video image is input into the trained second KNN classifier for analysis, so that it can be determined whether the region of interest is a black screen image.
In the seventh embodiment of the present invention, the degradation detection module 30 includes:
and the third detection submodule 33 is configured to establish a third KNN classifier, analyze the region of interest in the video image through the third KNN classifier, and detect whether the region of interest is a flower screen image.
In this embodiment, the screenful image dataset of the screen may be trained as training data of the third KNN classifier, and the region of interest in the video image is input into the trained third KNN classifier for analysis, so as to determine whether the region of interest is a screenful image.
In an eighth embodiment of the present invention, when the aging detection performed on the region of interest in the video image is a screen fixing detection, a first predetermined number of consecutive video images are acquired, and the aging detection module 30 includes:
a fourth detection sub-module 34, configured to, in the consecutive video images, combine two adjacent video images into an image group; and performing similarity detection on the interested region of the video image in the image group, determining that the screen is aged at a fixed screen when the similarity detection result is that the number of groups of similar video images is greater than a threshold value, and otherwise, determining that the screen is normal.
In this embodiment, when the screen crashes, a screen-fixing phenomenon occurs, and the screen maintains to display the same picture. The method comprises the steps of obtaining a first preset number of continuous video images, wherein the first preset number is set according to actual requirements, and judging whether the screen is fixed by judging whether the interested areas of the continuous video images are similar.
Fig. 3 is a flowchart of a method for detecting an aged screen, which can be implemented by the system 100 described in any one of the above embodiments, according to an embodiment of the present invention, and the method for detecting an aged screen includes:
step S301, monitoring and collecting the video image of the screen; realized by the image acquisition module 10;
step S302, setting a region corresponding to the screen in the video image as an interested region; by the region selection module 20;
step S303, carrying out aging detection on the region of interest in the video image to obtain an aging detection result; by the degradation detection module 30.
In this embodiment, the method may be implemented by using the system 100 described in any one of the above, and for a specific implementation process, reference is made to the above description, which is not described herein again.
In an embodiment of the present invention, after step S303, the method further includes:
analyzing the aging detection result, and sending alarm information if the aging detection result indicates that the screen has an aging phenomenon; by the alarm module 40.
In an embodiment of the present invention, after step S303, the method further includes:
storing the aging detection result and the video image corresponding to the aging detection result; by the memory module 50.
In one embodiment of the present invention, when the video image contains a plurality of the screens, an area containing the plurality of the screens in the video image is set as the region of interest;
the step S303 includes:
performing image segmentation on the region of interest in the video image, wherein the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen; by the image segmentation module 60;
the step S303 includes:
respectively carrying out aging detection on each target area to obtain an aging detection result of the screen corresponding to each target area; by the first detection submodule 31.
In an embodiment of the present invention, the video image is analyzed by a first KNN classifier, a foreground image of the video image is identified, the foreground image is an area corresponding to the screen, the foreground image is set as the area of interest, and the method is implemented by an area selection module 20.
In one embodiment of the present invention, the step S303 includes:
establishing a second KNN classifier, analyzing the interested region in the video image through the second KNN classifier, and detecting whether the interested region is a black screen image; by the second detection submodule 32.
In an embodiment of the present invention, the step S303 includes:
establishing a third KNN classifier, analyzing the region of interest in the video image through the third KNN classifier, and detecting whether the region of interest is a screen image; by a third detection submodule 33.
In an embodiment of the present invention, when the aging detection performed on the region of interest in the video image is a screen fixing detection, a first predetermined number of consecutive video images are acquired, and the step S303 includes:
in the continuous video images, two adjacent video images form an image group;
performing similarity detection on the region of interest of the video images in the image group, and determining that the screen is aged in a fixed screen mode when the similarity detection result is that the number of groups of similar video images is greater than a threshold value, otherwise, determining that the screen is normal; by a fourth detection sub-module 34.
The present invention also provides a storage medium storing a computer program for executing any one of the above-described aged screen detection methods. Such as computer program instructions, which when executed by a computer, may invoke or otherwise provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on fixed or removable storage media and/or transmitted via a data stream over a broadcast or other signal-bearing medium and/or stored on a storage medium of a computer device operating in accordance with the program instructions. Here, according to an embodiment of the present application, a computer device 400 as shown in fig. 4 is included, the computer device 400 preferably includes a storage medium 200 for storing a computer program and a processor 300 for executing the computer program, wherein when the computer program is executed by the processor 300, the computer device 400 is triggered to execute the method and/or the technical solution according to the foregoing embodiments.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the above steps or functions. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Further, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
The method according to the invention can be implemented on a computer as a computer-implemented method, or in dedicated hardware, or in a combination of both. Executable code for the method according to the invention or parts thereof may be stored on a computer program product. Examples of computer program products include memory devices, optical storage devices, integrated circuits, servers, online software, and so forth. Preferably, the computer program product comprises non-transitory program code means stored on a computer readable medium for performing the method according to the invention when said program product is executed on a computer.
In a preferred embodiment, the computer program comprises computer program code means adapted to perform all the steps of the method according to the invention when the computer program is run on a computer. Preferably, the computer program is embodied on a computer readable medium.
In summary, the invention sets the area corresponding to the screen in the video image as the region of interest by monitoring and collecting the video image of the screen; and carrying out aging detection on the region of interest in the video image to obtain an aging detection result. Through the analysis of the video image containing the screen, the process of screen aging is manually detected and converted into a process which can be processed by a computer, so that manual intervention is reduced, the screen aging phenomenon is automatically identified, and the detection accuracy and the data reliability are improved.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it should be understood that various changes and modifications can be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
The invention also discloses A1, a method for detecting the aged screen, which comprises the following steps:
monitoring and collecting the video image of the screen;
setting a region corresponding to the screen in the video image as a region of interest;
and carrying out aging detection on the region of interest in the video image to obtain an aging detection result.
A2, the method for detecting aged screens according to a1, further comprising after the step of obtaining the aged detection results:
and analyzing the aging detection result, and sending alarm information if the aging detection result indicates that the screen has an aging phenomenon.
A3, the method for detecting an aged screen according to a1, further comprising after the step of obtaining an aged detection result:
and storing the aging detection result and the video image corresponding to the aging detection result.
A4, setting an area containing a plurality of said screens in said video image as said region of interest when said video image contains a plurality of said screens according to the method for detecting an aged screen described in a 1;
the step of detecting aging of the region of interest in the video image comprises:
performing image segmentation on the region of interest in the video image, wherein the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen;
the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises:
and respectively carrying out aging detection on each target area to obtain an aging detection result of the screen corresponding to each target area.
A5, according to the aged screen detection method of A1, analyzing the video image through a first KNN classifier, identifying a foreground image of the video image, wherein the foreground image is an area corresponding to the screen, and the foreground image is set as the area of interest.
A6, according to the method for detecting an aged screen in A1, the step of performing aging detection on the region of interest in the video image and obtaining an aging detection result includes:
and establishing a second KNN classifier, analyzing the interested region in the video image through the second KNN classifier, and detecting whether the interested region is a black screen image.
A7, according to the detecting method of the aged screen in A1, the aging detection of the region of interest in the video image, the step of obtaining the aging detection result includes:
establishing a third KNN classifier, analyzing the interested region in the video image through the third KNN classifier, and detecting whether the interested region is a screen image.
A8, according to the aged screen detection method of a1, when the aging detection of the region of interest in the video image is a fixed screen detection, acquiring a first predetermined number of consecutive video images, and the aging detection of the region of interest in the video images, the step of acquiring an aging detection result includes:
in the continuous video images, two adjacent video images form an image group;
and performing similarity detection on the interested region of the video image in the image group, determining that the screen is aged at a fixed screen when the similarity detection result is that the number of groups of similar video images is greater than a threshold value, and otherwise, determining that the screen is normal.
B9, a system for detecting an aged screen, comprising:
the image acquisition module is used for monitoring and acquiring the video image of the screen;
the area selection module is used for setting an area corresponding to the screen in the video image as an area of interest;
and the aging detection module is used for carrying out aging detection on the region of interest in the video image to obtain an aging detection result.
B10, the system for detecting an aged screen according to B9, further comprising:
and the warning module is used for analyzing the aging detection result and sending warning information if the aging detection result indicates that the screen has an aging phenomenon.
B11, the system for detecting an aged screen according to B9, further comprising:
and the storage module is used for storing the aging detection result and the video image corresponding to the aging detection result.
B12, when the video image contains a plurality of screens, setting the area containing the plurality of screens in the video image as the region of interest according to the detection system of the aged screen of B9;
the system further comprises:
the image segmentation module is used for carrying out image segmentation on the region of interest in the video image, the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen;
the aging detection module includes:
and the first detection submodule is used for respectively carrying out aging detection on each target area to obtain an aging detection result of the screen corresponding to each target area.
B13, according to the aged screen detection system of B9, the region selection module establishes a first KNN classifier, analyzes the video image through the first KNN classifier, identifies a foreground image of the video image, the foreground image is a region corresponding to the screen, and the foreground image is set as the region of interest.
B14, the system for detecting aged screens according to B9, the aged detection module comprising:
and the second detection submodule is used for establishing a second KNN classifier, analyzing the interested area in the video image through the second KNN classifier and detecting whether the interested area is a black screen image.
B15, the system for detecting aged screens according to B9, the aged detection module comprising:
and the third detection submodule is used for establishing a third KNN classifier, analyzing the interested area in the video image through the third KNN classifier and detecting whether the interested area is a screen image.
B16, according to the aged screen detection system of B9, when the aging detection of the region of interest in the video image is a screen-fixing detection, acquiring a first predetermined number of consecutive video images, the aging detection module comprising:
the fourth detection submodule is used for forming an image group by two adjacent video images in the continuous video images; and performing similarity detection on the region of interest of the video images in the image group, and determining that the screen is aged in a fixed screen mode when the similarity detection result is that the number of groups of similar video images is greater than a threshold value, otherwise, determining that the screen is normal.
C17, a storage medium, characterized by storing a computer program for executing a method of detecting an aged screen of any one of a1 to a 8.
D18, a computer device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the method for detecting an aged screen according to any one of a1 to a8 when executing the computer program.

Claims (10)

1. A method for detecting an aged screen, comprising:
monitoring and collecting the video image of the screen;
setting a region corresponding to the screen in the video image as an interested region;
and carrying out aging detection on the region of interest in the video image to obtain an aging detection result.
2. The method for detecting an aged screen according to claim 1, wherein the step of obtaining an aged detection result further comprises, after:
and analyzing the aging detection result, and sending alarm information if the aging detection result indicates that the screen has an aging phenomenon.
3. The method for detecting an aged screen according to claim 1, wherein the step of obtaining an aged detection result further comprises, after:
and storing the aging detection result and the video image corresponding to the aging detection result.
4. The method for detecting an aged screen according to claim 1, wherein when the video image contains a plurality of the screens, an area containing the plurality of the screens in the video image is set as the region of interest;
the step of detecting aging of the region of interest in the video image comprises:
performing image segmentation on the region of interest in the video image, wherein the region of interest is segmented into a plurality of target regions, and each target region corresponds to each screen;
the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises:
and respectively carrying out aging detection on each target area to obtain an aging detection result of the screen corresponding to each target area.
5. The method for detecting an aged screen according to claim 1, wherein the video image is analyzed by a first KNN classifier, a foreground image of the video image is identified, the foreground image is a region corresponding to the screen, and the foreground image is set as the region of interest.
6. The method for detecting an aged screen according to claim 1, wherein the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises:
and establishing a second KNN classifier, analyzing the interested region in the video image through the second KNN classifier, and detecting whether the interested region is a black screen image.
7. The method for detecting an aged screen according to claim 1, wherein the step of performing aging detection on the region of interest in the video image to obtain an aging detection result comprises:
establishing a third KNN classifier, analyzing the interested region in the video image through the third KNN classifier, and detecting whether the interested region is a screen image.
8. A system for detecting an aged screen, comprising:
the image acquisition module is used for monitoring and acquiring the video image of the screen;
the area selection module is used for setting an area corresponding to the screen in the video image as an area of interest;
and the aging detection module is used for carrying out aging detection on the interested region in the video image to obtain an aging detection result.
9. A storage medium for storing a computer program for executing a method of detecting an aged screen according to any one of claims 1 to 7.
10. A computer device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the method for detecting an aged screen according to any one of claims 1 to 7 when executing the computer program.
CN202011318928.6A 2020-11-23 2020-11-23 Method, system, storage medium, and computer device for detecting aged screen Pending CN114529497A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117110763A (en) * 2023-10-12 2023-11-24 广州伊索自动化科技有限公司 Aging detection system and method for automobile electronic product and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117110763A (en) * 2023-10-12 2023-11-24 广州伊索自动化科技有限公司 Aging detection system and method for automobile electronic product and storage medium
CN117110763B (en) * 2023-10-12 2024-03-08 广州伊索自动化科技有限公司 Aging detection system and method for automobile electronic product and storage medium

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