CN117830320A - Display screen display abnormality detection method and system based on image recognition - Google Patents
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Abstract
The invention discloses a display abnormality detection method and a display abnormality detection system for a display screen based on image recognition, which relate to the technical field of display screens and comprise the following steps: obtaining a first characteristic image and a second characteristic image; taking the rest image of at least one image as a verification image; obtaining at least one suspected abnormal region; judging whether the images of the suspected abnormal region in at least one verification image are consistent or not, and judging whether the images of the suspected abnormal region in at least one verification image are one of a first verification image or a second verification image or not; if at least one suspected abnormal region is a display normal region, judging that the display screen is normal in display, and if one suspected abnormal region is a display abnormal region, judging that the display screen is abnormal in display. By arranging the feature extraction module, the abnormality detection module and the judgment module, the display screen equipment can be timely maintained after abnormality reporting, and the service life of the display screen equipment is prolonged.
Description
Technical Field
The invention relates to the technical field of display screens, in particular to a display screen display abnormality detection method and system based on image recognition.
Background
Display screen devices are widely used as advertising machines installed in places where the flow of people is large, such as elevators, public transportation means, and waiting rooms, for delivering pictures or video advertisements, and are uniformly managed and maintained by advertisement operators.
When the display screen device is abnormal, the display screen device is usually a partial area black screen, a white screen or a flickering flicker, wherein the flickering flicker is to switch and display a brighter image and a darker image at a certain frequency. The display screen is usually overhauled by adopting a round-robin mode, namely, the display screen equipment is overhauled at intervals, or the display screen equipment is maintained after abnormal reporting by related responsible personnel at the installation point. But this way also cannot find out the abnormal situation of the display screen in time. Since the abnormality is not found timely and is not maintained timely, the life of the display screen device is easily shortened.
Disclosure of Invention
In order to solve the technical problems, the technical scheme provides a display abnormality detection method and system for a display screen based on image recognition, and the technical scheme solves the problem that the display screen provided in the background art usually adopts a round-robin mode, namely, the display screen equipment is overhauled at intervals, or the relevant responsible personnel at the installation point repair after abnormality report of the display screen equipment. But this way also cannot find out the abnormal situation of the display screen in time. The problem that the service life of the display screen device is easily shortened because the abnormality is not found timely and is not maintained timely.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a display screen display abnormality detection method based on image recognition comprises the following steps:
acquiring at least one continuously played image of a display screen, and carrying out RGB three-color modeling on the at least one image to obtain an RGB value of each pixel point in the at least one image;
performing difference comparison in at least one image to obtain at least one group of first characteristic image and second characteristic image;
taking the rest image of at least one image as a verification image;
the same feature extraction is carried out on the first feature image and the second feature image, so that at least one suspected abnormal region is obtained;
detecting the abnormality of the suspected abnormal region in the at least one verification image, judging whether the images of the suspected abnormal region in the at least one verification image are consistent, if yes, judging the suspected abnormal region as a display abnormal region, if no, acquiring two images of the suspected abnormal region inconsistent in the at least one verification image as a first verification image and a second verification image, judging whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image, if yes, judging the suspected abnormal region as a display abnormal region, and if no, judging the suspected abnormal region as a display normal region;
if at least one suspected abnormal region is a display normal region, judging that the display screen is normal in display, and if one suspected abnormal region is a display abnormal region, judging that the display screen is abnormal in display.
Preferably, the performing the difference comparison in at least one image to obtain at least one set of the first feature image and the second feature image includes the following steps:
acquiring a first image and a second image in at least one frame of image;
calculating an image pixel difference value of the first image and the second image;
taking the pixel value difference of the pixel points at the same position in the first image and the second image and taking the absolute value to obtain the pixel value difference;
accumulating all pixel value differences to obtain image pixel difference values of the first image and the second image;
judging whether the pixel difference value of the image is larger than a preset value, if so, taking the first video frame image and the second video frame image as a first characteristic image and a second characteristic image respectively, and if not, performing no processing.
Preferably, the step of extracting the same features from the first feature image and the second feature image to obtain at least one suspected abnormal region includes the following steps:
the RGB values of pixel points at the same position are subjected to difference in the first characteristic image and the second characteristic image, and absolute values are taken to obtain RGB difference values;
acquiring pixel points with RGB difference values smaller than a preset value as the same characteristic points;
and classifying the same characteristic points with the distance smaller than the preset distance into the same region to obtain at least one suspected abnormal region.
Preferably, the determining whether the image of the suspected abnormal region in the at least one verification image is uniform or not includes the steps of:
acquiring an image of a suspected abnormal region in at least one verification image as a suspected region image;
acquiring a first suspected region image and a second suspected region image in at least one suspected region image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the second suspected region image, and taking an absolute value to obtain an RGB suspected difference value;
accumulating the RGB suspected difference values to obtain a suspected region judgment value;
judging whether the suspicious region judgment value is larger than a preset value, if so, enabling the first suspicious region image to be inconsistent with the second suspicious region image, and if not, enabling the first suspicious region image to be consistent with the second suspicious region image;
traversing all image combinations in at least one suspicious region image by the first suspicious region image and the second suspicious region image, judging that the images of the suspicious abnormal region in the at least one verification image are consistent if the first suspicious region image and the second suspicious region image are consistent, and judging that the images of the suspicious abnormal region in the at least one verification image are inconsistent if the images of the suspicious abnormal region are not consistent.
Preferably, the step of judging whether the image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image includes the steps of:
acquiring an image of the suspected abnormal region in at least one verification image as a third verification image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the third suspected region image, and taking an absolute value to obtain a first RGB difference value;
accumulating the first RGB difference values to obtain first RGB judgment difference values;
calculating the difference of RGB values of pixel points at the same position in the second suspected region image and the third suspected region image, and taking an absolute value to obtain a second RGB difference value;
accumulating the second RGB difference value to obtain a second RGB judgment difference value;
judging whether the first RGB judgment difference value or the second RGB judgment difference value is smaller than a preset value, if yes, the third verification image is one of the first verification image or the second verification image, and if no, no processing is carried out;
the third verification image traverses the images of the suspected abnormal region in the at least one verification image, if the third verification image is one of the first verification image or the second verification image, the images of the suspected abnormal region in the at least one verification image are judged to be one of the first verification image or the second verification image, and if the third verification image is not one of the first verification image or the second verification image, no processing is carried out.
The display screen display abnormality detection system based on image recognition is used for realizing the display screen display abnormality detection method based on image recognition, and comprises the following steps:
the image acquisition module acquires at least one continuously played image of the display screen;
the RGB modeling module is used for carrying out RGB three-color modeling on at least one image to obtain an RGB value of each pixel point in the at least one image;
the image comparison module is used for performing difference comparison in at least one image to obtain at least one group of first characteristic images and second characteristic images;
the feature extraction module is used for carrying out the same feature extraction on the first feature image and the second feature image to obtain at least one suspected abnormal region;
the abnormality detection module is used for detecting the abnormality of the suspected abnormal region in at least one verification image;
the judging module judges whether the images of the suspected abnormal region in the at least one verification image are consistent or not, and judges whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image or not.
Compared with the prior art, the invention has the beneficial effects that:
through setting up feature extraction module, unusual detection module and judgement module, can distinguish judgement to black screen, white screen or sudden and suddenly flickering to judge the display screen under the different conditions independently, and then obtain whether there is the abnormality in the display screen, thereby can in time maintain after reporting the unusual emergence of display screen equipment, and then guarantee at the unusual initial stage of display screen, just discover the abnormality, and handle the abnormality, extension display screen equipment's life-span.
Drawings
FIG. 1 is a flow chart of a display abnormality detection method of a display screen based on image recognition;
FIG. 2 is a flow chart of the present invention for performing a difference comparison in at least one image to obtain at least one set of a first feature image and a second feature image;
FIG. 3 is a schematic flow chart of the method for extracting the same features of the first feature image and the second feature image to obtain at least one suspected abnormal region;
FIG. 4 is a schematic flow chart for judging whether images of a suspected abnormal region in at least one verification image are uniform or not;
fig. 5 is a flowchart illustrating a process of determining whether an image of a suspected abnormal region in at least one verification image is one of a first verification image or a second verification image according to the present invention.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, a method for detecting abnormal display on a display screen based on image recognition includes:
acquiring at least one continuously played image of a display screen, and carrying out RGB three-color modeling on the at least one image to obtain an RGB value of each pixel point in the at least one image;
performing difference comparison in at least one image to obtain at least one group of first characteristic image and second characteristic image;
taking the rest image of at least one image as a verification image;
the same feature extraction is carried out on the first feature image and the second feature image, so that at least one suspected abnormal region is obtained;
detecting the abnormality of the suspected abnormal region in the at least one verification image, judging whether the images of the suspected abnormal region in the at least one verification image are consistent, if yes, judging the suspected abnormal region as a display abnormal region, if no, acquiring two images of the suspected abnormal region inconsistent in the at least one verification image as a first verification image and a second verification image, judging whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image, if yes, judging the suspected abnormal region as a display abnormal region, and if no, judging the suspected abnormal region as a display normal region;
if at least one suspected abnormal region is a display normal region, judging that the display screen is normal in display, and if one suspected abnormal region is a display abnormal region, judging that the display screen is abnormal in display.
Referring to fig. 2, performing a difference comparison in at least one image to obtain at least one set of a first feature image and a second feature image includes the steps of:
acquiring a first image and a second image in at least one frame of image;
calculating an image pixel difference value of the first image and the second image;
taking the pixel value difference of the pixel points at the same position in the first image and the second image and taking the absolute value to obtain the pixel value difference;
accumulating all pixel value differences to obtain image pixel difference values of the first image and the second image;
judging whether the pixel difference value of the image is larger than a preset value, if so, taking the first video frame image and the second video frame image as a first characteristic image and a second characteristic image respectively, and if not, not performing any treatment;
the method comprises the steps of performing difference comparison in at least one image to obtain at least one group of first characteristic images and second characteristic images, wherein the purpose of finding different images in at least one frame of images is to find out that the first characteristic images and the second characteristic images are different, and the display screen displays a black screen, a white screen or a flicker screen when faults exist, wherein the images of the black screen and the white screen are single, and the images of the flicker screen are bright and dark;
therefore, in the first characteristic image and the second characteristic image which are different, the same region is the image of the black screen and the white screen, and the same characteristic extraction is carried out and can be used as a suspected abnormal region;
when there are multiple sets of first feature images and second feature images, the flicker screen images of the first feature images and the second feature images must be bright or dark at the same time, so that the same feature extraction is performed to be used as a suspected abnormal region.
Referring to fig. 3, performing the same feature extraction on the first feature image and the second feature image to obtain at least one suspected abnormal region includes the following steps:
the RGB values of pixel points at the same position are subjected to difference in the first characteristic image and the second characteristic image, and absolute values are taken to obtain RGB difference values;
acquiring pixel points with RGB difference values smaller than a preset value as the same characteristic points;
classifying the same characteristic points with the distance smaller than the preset distance into the same region to obtain at least one suspected abnormal region;
when the first characteristic image and the second characteristic image are subjected to the same characteristic extraction, first, the same pixel points are obtained, and the pixel points are aggregated to obtain a suspected abnormal region.
Referring to fig. 4, determining whether the image of the suspected abnormal region in the at least one verification image is uniform includes the steps of:
acquiring an image of a suspected abnormal region in at least one verification image as a suspected region image;
acquiring a first suspected region image and a second suspected region image in at least one suspected region image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the second suspected region image, and taking an absolute value to obtain an RGB suspected difference value;
accumulating the RGB suspected difference values to obtain a suspected region judgment value;
judging whether the suspicious region judgment value is larger than a preset value, if so, enabling the first suspicious region image to be inconsistent with the second suspicious region image, and if not, enabling the first suspicious region image to be consistent with the second suspicious region image;
traversing all image combinations in at least one suspected region image by the first suspected region image and the second suspected region image, judging that the images of the suspected abnormal region in the at least one verification image are consistent if the first suspected region image and the second suspected region image are consistent, and judging that the images of the suspected abnormal region in the at least one verification image are inconsistent if the images of the suspected abnormal region are not consistent;
the purpose of judging whether the images in the suspected abnormal region are consistent in at least one verification image is to detect the condition of a black screen or a white screen, and when the suspected abnormal region is the condition of the black screen or the white screen, the images in the at least one verification image are both the black screen or the white screen, so that the images are consistent necessarily.
Referring to fig. 5, determining whether an image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image includes the steps of:
acquiring an image of the suspected abnormal region in at least one verification image as a third verification image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the third suspected region image, and taking an absolute value to obtain a first RGB difference value;
accumulating the first RGB difference values to obtain first RGB judgment difference values;
calculating the difference of RGB values of pixel points at the same position in the second suspected region image and the third suspected region image, and taking an absolute value to obtain a second RGB difference value;
accumulating the second RGB difference value to obtain a second RGB judgment difference value;
judging whether the first RGB judgment difference value or the second RGB judgment difference value is smaller than a preset value, if yes, the third verification image is one of the first verification image or the second verification image, and if no, no processing is carried out;
traversing the image of the suspected abnormal region in at least one verification image by the third verification image, judging that the image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image if the third verification image is one of the first verification image or the second verification image, and if the third verification image is not one of the first verification image or the second verification image, not performing any processing;
the purpose of judging whether the image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image is to detect the condition of the flicker screen, and the flicker screen is the same bright image and dark image, and the two conditions respectively correspond to the first verification image or the second verification image, so when the suspected abnormal region is the flicker screen, the image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image, and therefore the suspected abnormal region can be taken as a judgment basis.
The display screen display abnormality detection system based on image recognition is used for realizing the display screen display abnormality detection method based on image recognition, and comprises the following steps:
the image acquisition module acquires at least one continuously played image of the display screen;
the RGB modeling module is used for carrying out RGB three-color modeling on at least one image to obtain an RGB value of each pixel point in the at least one image;
the image comparison module is used for performing difference comparison in at least one image to obtain at least one group of first characteristic images and second characteristic images;
the feature extraction module is used for carrying out the same feature extraction on the first feature image and the second feature image to obtain at least one suspected abnormal region;
the abnormality detection module is used for detecting the abnormality of the suspected abnormal region in at least one verification image;
the judging module judges whether the images of the suspected abnormal region in the at least one verification image are consistent or not, and judges whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image or not.
The working process of the display screen display abnormality detection system based on image recognition is as follows:
step one: the method comprises the steps that an image acquisition module acquires at least one continuously played image of a display screen, and an RGB modeling module carries out RGB three-color modeling on the at least one image to obtain an RGB value of each pixel point in the at least one image;
step two: the image comparison module performs difference comparison in at least one image to obtain at least one group of first characteristic images and second characteristic images;
step three: taking the rest image of at least one image as a verification image;
step four: the feature extraction module performs the same feature extraction on the first feature image and the second feature image to obtain at least one suspected abnormal region;
step five: the abnormality detection module detects abnormality of the suspected abnormality area in at least one verification image, the judgment module judges whether the images of the suspected abnormality area in the at least one verification image are consistent, if yes, the suspected abnormality area is judged to be a display abnormality area, if not, two images of the suspected abnormality area, which are inconsistent in the at least one verification image, are obtained and used as a first verification image and a second verification image, the judgment module judges whether the images of the suspected abnormality area in the at least one verification image are one of the first verification image and the second verification image, if yes, the suspected abnormality area is judged to be a display abnormality area, and if not, the suspected abnormality area is judged to be a display normal area;
step six: if at least one suspected abnormal region is a display normal region, judging that the display screen is normal in display, and if one suspected abnormal region is a display abnormal region, judging that the display screen is abnormal in display.
Still further, the present disclosure provides a storage medium having a computer readable program stored thereon, where the computer readable program executes the above-described method for detecting display abnormality of a display screen based on image recognition when called.
It is understood that the storage medium may be a magnetic medium, e.g., floppy disk, hard disk, magnetic tape; optical media such as DVD; or a semiconductor medium such as a solid state disk SolidStateDisk, SSD, etc.
In summary, the invention has the advantages that: through setting up feature extraction module, unusual detection module and judgement module, can distinguish judgement to black screen, white screen or sudden and suddenly flickering to judge the display screen under the different conditions independently, and then obtain whether there is the abnormality in the display screen, thereby can in time maintain after reporting the unusual emergence of display screen equipment, and then guarantee at the unusual initial stage of display screen, just discover the abnormality, and handle the abnormality, extension display screen equipment's life-span.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The display abnormality detection method for the display screen based on the image recognition is characterized by comprising the following steps of:
acquiring at least one continuously played image of a display screen, and carrying out RGB three-color modeling on the at least one image to obtain an RGB value of each pixel point in the at least one image;
performing difference comparison in at least one image to obtain at least one group of first characteristic image and second characteristic image;
taking the rest image of at least one image as a verification image;
the same feature extraction is carried out on the first feature image and the second feature image, so that at least one suspected abnormal region is obtained;
detecting the abnormality of the suspected abnormal region in the at least one verification image, judging whether the images of the suspected abnormal region in the at least one verification image are consistent, if yes, judging the suspected abnormal region as a display abnormal region, if no, acquiring two images of the suspected abnormal region inconsistent in the at least one verification image as a first verification image and a second verification image, judging whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image, if yes, judging the suspected abnormal region as a display abnormal region, and if no, judging the suspected abnormal region as a display normal region;
if at least one suspected abnormal region is a display normal region, judging that the display screen is normal in display, and if one suspected abnormal region is a display abnormal region, judging that the display screen is abnormal in display.
2. The method for detecting abnormal display on a display screen based on image recognition according to claim 1, wherein the performing difference comparison in at least one image to obtain at least one set of a first feature image and a second feature image comprises the steps of:
acquiring a first image and a second image in at least one frame of image;
calculating an image pixel difference value of the first image and the second image;
taking the pixel value difference of the pixel points at the same position in the first image and the second image and taking the absolute value to obtain the pixel value difference;
accumulating all pixel value differences to obtain image pixel difference values of the first image and the second image;
judging whether the pixel difference value of the image is larger than a preset value, if so, taking the first video frame image and the second video frame image as a first characteristic image and a second characteristic image respectively, and if not, performing no processing.
3. The method for detecting abnormal display on a display screen based on image recognition according to claim 2, wherein the step of extracting the same features from the first feature image and the second feature image to obtain at least one suspected abnormal region comprises the steps of:
the RGB values of pixel points at the same position are subjected to difference in the first characteristic image and the second characteristic image, and absolute values are taken to obtain RGB difference values;
acquiring pixel points with RGB difference values smaller than a preset value as the same characteristic points;
and classifying the same characteristic points with the distance smaller than the preset distance into the same region to obtain at least one suspected abnormal region.
4. A method for detecting abnormal display on a display screen based on image recognition according to claim 3, wherein said judging whether the images of the suspected abnormal region in the at least one verification image are uniform or not comprises the steps of:
acquiring an image of a suspected abnormal region in at least one verification image as a suspected region image;
acquiring a first suspected region image and a second suspected region image in at least one suspected region image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the second suspected region image, and taking an absolute value to obtain an RGB suspected difference value;
accumulating the RGB suspected difference values to obtain a suspected region judgment value;
judging whether the suspicious region judgment value is larger than a preset value, if so, enabling the first suspicious region image to be inconsistent with the second suspicious region image, and if not, enabling the first suspicious region image to be consistent with the second suspicious region image;
traversing all image combinations in at least one suspicious region image by the first suspicious region image and the second suspicious region image, judging that the images of the suspicious abnormal region in the at least one verification image are consistent if the first suspicious region image and the second suspicious region image are consistent, and judging that the images of the suspicious abnormal region in the at least one verification image are inconsistent if the images of the suspicious abnormal region are not consistent.
5. The method for detecting abnormal display on a display screen based on image recognition according to claim 4, wherein the step of judging whether the image of the suspected abnormal region in the at least one verification image is one of the first verification image or the second verification image comprises the steps of:
acquiring an image of the suspected abnormal region in at least one verification image as a third verification image;
calculating the difference of RGB values of pixel points at the same position in the first suspected region image and the third suspected region image, and taking an absolute value to obtain a first RGB difference value;
accumulating the first RGB difference values to obtain first RGB judgment difference values;
calculating the difference of RGB values of pixel points at the same position in the second suspected region image and the third suspected region image, and taking an absolute value to obtain a second RGB difference value;
accumulating the second RGB difference value to obtain a second RGB judgment difference value;
judging whether the first RGB judgment difference value or the second RGB judgment difference value is smaller than a preset value, if yes, the third verification image is one of the first verification image or the second verification image, and if no, no processing is carried out;
the third verification image traverses the images of the suspected abnormal region in the at least one verification image, if the third verification image is one of the first verification image or the second verification image, the images of the suspected abnormal region in the at least one verification image are judged to be one of the first verification image or the second verification image, and if the third verification image is not one of the first verification image or the second verification image, no processing is carried out.
6. A display screen display abnormality detection system based on image recognition for realizing the display screen display abnormality detection method based on image recognition according to any one of claims 1 to 5, comprising:
the image acquisition module acquires at least one continuously played image of the display screen;
the RGB modeling module is used for carrying out RGB three-color modeling on at least one image to obtain an RGB value of each pixel point in the at least one image;
the image comparison module is used for performing difference comparison in at least one image to obtain at least one group of first characteristic images and second characteristic images;
the feature extraction module is used for carrying out the same feature extraction on the first feature image and the second feature image to obtain at least one suspected abnormal region;
the abnormality detection module is used for detecting the abnormality of the suspected abnormal region in at least one verification image;
the judging module judges whether the images of the suspected abnormal region in the at least one verification image are consistent or not, and judges whether the images of the suspected abnormal region in the at least one verification image are one of the first verification image or the second verification image or not.
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| US20190266437A1 (en) * | 2016-12-15 | 2019-08-29 | Federal Home Loan Mortgage Corporation | System, device, and method for image anomaly detection |
| CN112396999A (en) * | 2019-08-16 | 2021-02-23 | 西安诺瓦星云科技股份有限公司 | Abnormal display block detection method, display screen fault detection method and equipment thereof |
| CN111289536A (en) * | 2020-04-07 | 2020-06-16 | 深圳回收宝科技有限公司 | Defect detection device of electronic equipment screen |
| US20220101764A1 (en) * | 2020-09-30 | 2022-03-31 | GE Precision Healthcare LLC | Methods and systems for detecting a malfunctioning display device |
| CN115861152A (en) * | 2021-09-24 | 2023-03-28 | 广州视源创新科技有限公司 | Method, system, device and medium for detecting defective area of display screen |
| CN115880213A (en) * | 2021-09-28 | 2023-03-31 | 华为技术有限公司 | Display abnormity detection method, device and system |
| CN115619743A (en) * | 2022-10-20 | 2023-01-17 | 华中科技大学 | Construction method and application of OLED novel display device surface defect detection model |
| CN117274211A (en) * | 2023-09-28 | 2023-12-22 | 深圳市前海研祥亚太电子装备技术有限公司 | Screen defect detection method and device, terminal equipment and storage medium |
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