CN113873232B - Video clamping detection method, device and system and storage medium - Google Patents
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Abstract
The invention relates to a video clamping detection method, which comprises the following steps: acquiring image information of target equipment in a detection time period, wherein the ending time of the detection time period is the current time; obtaining a neighbor similarity value by utilizing a structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the last moment; obtaining an average similarity value of the acquired images in the detection time period by using the SSIM and the image information; and judging whether video jamming occurs to the target equipment in the detection time period according to the neighbor similarity value, the average similarity value, the neighbor similarity threshold and the average similarity threshold. According to the invention, by monitoring the video picture of the screen of the target equipment in the detection time period and utilizing the structural similarity algorithm, whether video clamping occurs or not is automatically judged, the testing efficiency is improved, and the labor cost is saved. The invention also relates to a device, a system and a storage medium for detecting video jamming.
Description
Technical Field
The present invention relates to the field of electronic technologies, and in particular, to a method, an apparatus, a system, and a storage medium for detecting video clip.
Background
When a video is watched on an intelligent device, sometimes video clamping phenomenon occurs due to insufficient network bandwidth or poor hardware performance, and the phenomenon affects user experience. Currently, when a technician is optimizing video clip, the technician watches video for a long time and counts the number of times and time points of video clip occurrence through a special tester, so that the optimization effect of video clip is evaluated, but the evaluation mode is low in efficiency and consumes huge labor cost.
Disclosure of Invention
The invention aims to solve the technical problem of providing a video clamping detection method, a device, a system and a storage medium aiming at the defects of the prior art.
The technical scheme for solving the technical problems is as follows:
a method of detecting video jams, the method comprising:
acquiring image information of target equipment in a detection time period, wherein the ending time of the detection time period is the current time;
obtaining a neighbor similarity value by utilizing a structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the last moment;
obtaining an average similarity value of the acquired images in the detection time period by using the SSIM and the image information;
and judging whether video clip occurs to the target equipment in the detection time period according to the neighbor similarity value, the average similarity value, a neighbor similarity threshold and the average similarity threshold.
The beneficial effects of the invention are as follows: the method and the device for detecting the video jamming of the target equipment in the detection time period can automatically judge whether the video jamming occurs or not by utilizing the structural similarity algorithm through monitoring the video picture of the screen of the target equipment in the detection time period, improve the testing efficiency and save the labor cost.
On the basis of the technical scheme, the invention can be improved as follows.
Further, the obtaining the average similarity of the acquired images in the detection time period by using the structural similarity algorithm and the image information specifically includes:
each preset step is pushed forward from the current moment to obtain a detection point, and a plurality of detection points are obtained in the detection time period, wherein the detection time period comprises a preset number of sampling time points, and the preset step is the duration of one or more sampling time points;
calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm;
and obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values.
The beneficial effects of adopting the further scheme are as follows: the average similarity value of the images obtained in the detection time period is more accurate in judging whether video jam occurs.
Further, the determining whether video clip occurs in the target device in the detection time period according to the neighbor similarity, the average similarity, a neighbor similarity threshold, and an average similarity threshold specifically includes:
when the neighbor similarity is larger than the neighbor similarity threshold and the average similarity is larger than the average similarity threshold, judging that video jamming occurs in the target device in the detection time period;
otherwise, judging that the target equipment does not have video jamming in the detection time period.
The beneficial effects of adopting the further scheme are as follows: the method for judging whether video jamming occurs in the target equipment in the detection time period or not is more accurate in judging the video jamming phenomenon, and missing judgment and misjudgment are reduced through the neighbor similarity, the average similarity, the neighbor similarity threshold and the average similarity threshold.
The other technical scheme for solving the technical problems is as follows:
a device for detecting video jams, the device comprising:
the acquisition module is used for acquiring the acquired image information of the target equipment in a detection time period, wherein the detection time period comprises a preset number of sampling moments, and the ending moment of the detection time period is the current moment;
the computing module is used for obtaining a neighbor similarity value by utilizing a structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the last moment;
obtaining average similarity of the acquired images in the detection time period by using a structural similarity algorithm and the image information;
and the judging module is used for judging whether video clamping of the target equipment occurs in the detection time period according to the neighbor similarity, the average similarity, a neighbor similarity threshold and an average similarity threshold.
The beneficial effects of the invention are as follows: the device comprises an acquisition module, a calculation module and a judgment module, wherein the acquisition module is used for acquiring a neighbor similarity value and an average similarity value according to acquired image information and a structural similarity algorithm of target equipment in a detection time period, judging whether video jamming occurs in the target equipment in the detection time period according to the neighbor similarity value, the average similarity value, a neighbor similarity threshold and the average similarity threshold, and automatically judging whether video jamming occurs or not by monitoring video pictures of a screen of the target equipment in the detection time period by utilizing the structural similarity algorithm, so that the testing efficiency is improved, and the labor cost is saved.
On the basis of the technical scheme, the invention can be improved as follows.
Further, the calculating module is specifically configured to push a preset step forward from the current time every time to obtain a detection point, and obtain a plurality of detection points in the detection time period, where the detection time period includes a preset number of sampling time points, and the preset step is a duration of one or more sampling time points;
calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm, wherein the preset time step is the duration of one or more sampling moments;
and obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values.
The beneficial effects of adopting the further scheme are as follows: the calculation module calculates the average similarity value of the images acquired in the detection time period, so that whether the video jam phenomenon occurs or not is more accurate.
Further, the judging module is specifically configured to judge that video clip occurs in the target device in the detection time period when the neighbor similarity value is greater than the neighbor similarity threshold and the average similarity value is greater than the average similarity threshold;
otherwise, judging that the target equipment does not have video clamping in the detection time period.
The beneficial effects of adopting the further scheme are as follows: the judging module judges whether the video jam occurs in the target equipment in the detection time period or not through the neighbor similarity, the average similarity, the neighbor similarity threshold and the average similarity threshold, so that the video jam phenomenon is more accurately judged, and missed judgment and misjudgment are reduced.
In addition, the invention provides a video jamming detection system, which comprises an image pickup device and a video jamming detection device according to any one of the technical schemes;
the camera equipment is connected with the video clamping detection device;
the image pickup device is used for collecting image information of the target device in a detection time period.
The present invention also provides a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the steps of the video clip detection method according to any one of the above-mentioned technical solutions.
Additional aspects of the invention 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 invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly explain the embodiments of the present invention or the drawings used in the description of the prior art, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flowchart of a video clip detection method according to an embodiment of the present invention;
fig. 2 is a block diagram of a video clip detecting device according to another embodiment of the present invention;
fig. 3 is a system structure diagram of a video clip detection system according to another embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
As shown in a schematic flowchart of a video-stuck detection method provided in the embodiment of the present invention in fig. 1, a video-stuck detection method includes the following steps:
110. image information of the target device in the detection time period is acquired.
It should be understood that the detection period includes a preset number of sampling time points, and the ending time of the detection period is the current time.
120. And obtaining a neighbor similarity value by utilizing the structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the last moment.
130. And obtaining the average similarity of the acquired images in the detection time period by using the SSIM and the image information.
140. And judging whether video jamming occurs to the target equipment in the detection time period according to the neighbor similarity, the average similarity, the neighbor similarity threshold and the average similarity threshold.
According to the video jamming detection method provided by the embodiment, the neighbor similarity value and the average similarity value are obtained through the obtained image information and the structural similarity algorithm of the target equipment in the detection time period, whether the video jamming of the target equipment occurs in the detection time period is judged according to the neighbor similarity value, the average similarity value, the neighbor similarity threshold value and the average similarity threshold value, and the video jamming of the screen of the target equipment in the detection time period is monitored.
Further, step 130 specifically includes:
131. each time a preset step is pushed forward from the current moment, a detection point is obtained, a plurality of detection points are obtained in a detection time period, wherein the detection time period comprises a preset number of sampling time points, and the preset step is the duration of one or more sampling time points.
132. And calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm.
133. And obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values.
Further, step 140 specifically includes:
141. when the neighbor similarity value is larger than the neighbor similarity threshold value and the average similarity value is larger than the average similarity threshold value, judging that video jamming occurs in the target equipment in the detection time period;
142. otherwise, judging that the target equipment does not have video clamping in the detection time period.
It should be appreciated that the structural similarity SSIM (Structural Similarity Index) is an index for measuring the similarity of two images, and has been widely used in the field of image quality evaluation.
Specifically, for example, when the image information of the target device acquired at the current time T is x and the image information acquired at the previous time T-T is y, the neighboring similarity value S of the images acquired at the current time and the previous time Cur (P t ) Can be obtained according to the following formula:
wherein mu x Is the average value of x, mu y Is the average value of y and is,
is the variance of x>
Is the variance of y, sigma xy Is the covariance of x and y, C 1 =(k 1 L) 2 C 2 =(k 2 L) 2 Is a constant for maintaining stability, L is the dynamic range of pixel values, k 1 =0.01,k 2 =0.03, the range of neighbor similarity values is [0,1 ]]When x and y are identical, the value of SSIM is 1.
Specifically, let the image information of the target device acquired at the current time t be P t 。
The length of the detection section is defined as N, N is a positive integer, and N is more than or equal to 2.
Average similarity value S avg (P t ) Image information P acquired for the current time t t With t-kT (k.epsilon.1, N]) Average structural similarity between images captured at time, i.e.
When S is Cur (P t ) > neighbor similarity threshold and S avg (P t ) When the average similarity threshold value is larger than the average similarity threshold value, the image acquired at the current moment is considered to be the same as the image acquired at the last moment in subjective perception, and is highly similar to the images acquired at the previous N sampling moments, that is, the video picture has no obvious subjective perception change in the whole detection time period, and the video clamping phenomenon occurs. In a typical application, a neighbor similarity threshold is set to 0.9 and an average similarity threshold is set to 0.8.
As shown in fig. 2, in another embodiment of the present invention, a block diagram of a video-stuck detecting device includes:
the acquisition module is used for acquiring image information of the target equipment in a detection time period, wherein the ending time of the detection time period is the current time;
the computing module is used for obtaining a neighbor similarity value by utilizing a structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the last moment;
obtaining average similarity of the acquired images in the detection time period by using a structural similarity algorithm and the image information;
and the judging module is used for judging whether video clamping of the target equipment occurs in the detection time period according to the neighbor similarity, the average similarity, a neighbor similarity threshold and an average similarity threshold.
According to the video clamping detection device provided by the embodiment, the video clamping detection device comprises an acquisition module, a calculation module and a judgment module, a neighbor similarity value and an average similarity value are obtained according to the acquired image information and a structural similarity algorithm of the target device in a detection time period, whether the target device is subjected to video clamping in the detection time period is judged according to the neighbor similarity value, the average similarity value, a neighbor similarity threshold and the average similarity threshold, and whether the video clamping occurs or not is automatically judged by monitoring a video picture of a screen of the target device in the detection time period and utilizing the structural similarity algorithm.
Further, the calculating module is specifically configured to push a preset step forward from the current time every time to obtain a detection point, and obtain a plurality of detection points in the detection time period, where the detection time period includes a preset number of sampling time points, and the preset step is a duration of one or more sampling time points;
calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm;
and obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values.
Further, the judging module is specifically configured to judge that video jamming occurs in the target device in the detection time period when the neighbor similarity value is greater than the neighbor similarity threshold and the average similarity value is greater than the average similarity threshold;
otherwise, judging that the target equipment does not have video clamping in the detection time period.
Fig. 3 is a system structural diagram of a video jamming detection system according to another embodiment of the present invention, where the video jamming detection system includes an image capturing apparatus and a video jamming detection device according to any one of the above technical solutions;
the camera equipment is connected with a video stuck detection device;
the image pickup apparatus collects image information of the target apparatus in a detection period.
The video-stuck detection device acquires image information of the target device in a detection time period, obtains a neighbor similarity value by utilizing a structural similarity algorithm SSIM and the image information respectively acquired at the current moment and the previous moment, obtains an average similarity value of the acquired images in the detection time period by utilizing the SSIM and the image information, and judges whether video-stuck occurs in the target device in the detection time period according to the neighbor similarity value, the average similarity value, a neighbor similarity threshold and the average similarity threshold. Of course, the image capturing apparatus may start capturing after receiving the command for capturing image information sent by the video clip detecting device.
For example, the camera is connected with the testing station through a USB, receives an instruction of the testing station, shoots video pictures of a screen of the tested device at fixed time intervals, and transmits the shot pictures back to the testing station.
The present invention also provides a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the steps of the video clip detection method according to any one of the above-mentioned technical solutions.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. A method for detecting video jams, the method comprising:
acquiring image information of target equipment in a detection time period, wherein the detection time period comprises a plurality of detection points, and the ending time of the detection time period is the current time;
obtaining a neighbor similarity value by utilizing a structural similarity algorithm and the image information respectively acquired at the current moment and the last moment;
calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm, and obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values;
and when the neighbor similarity value is larger than a neighbor similarity threshold value and the average similarity value is larger than an average similarity threshold value, judging that video jamming occurs in the target equipment in the detection time period.
2. The method according to claim 1, wherein each time a preset step is pushed forward from the current time, a detection point is obtained, and the detection points are obtained in the detection time period.
3. The method for detecting video clip according to claim 2, wherein the number of detection points is greater than or equal to 2.
4. A method of detecting video clip according to any of claims 1-3, wherein the neighbor similarity threshold is 0.9 and the average similarity threshold is 0.8.
5. A video clip detection apparatus, the apparatus comprising:
the device comprises an acquisition module, a detection module and a display module, wherein the acquisition module is used for acquiring image information of target equipment in a detection time period, the detection time period comprises a plurality of detection points, and the ending time of the detection time period is the current time;
the calculation module is used for obtaining a neighbor similarity value by utilizing a structure similarity algorithm and the image information respectively acquired at the current moment and the last moment; calculating the structural similarity value of the image information acquired by each detection point and the image information acquired at the current moment by using a structural similarity algorithm, and obtaining the average similarity value of the acquired images in the detection time period according to all the structural similarity values;
and the judging module is used for judging that video clamping of the target equipment occurs in the detection time period when the neighbor similarity value is larger than a neighbor similarity threshold value and the average similarity value is larger than an average similarity threshold value.
6. The video clip detecting apparatus as defined in claim 5, wherein,
the calculation module is specifically configured to push a preset step length forward from the current time every time to obtain a detection point, and obtain the plurality of detection points in the detection time period.
7. The video clip detection apparatus of claim 6, wherein the number of detection points is greater than or equal to 2.
8. The video clip detection apparatus according to any one of claims 5-7, wherein the neighbor similarity threshold is 0.9 and the average similarity threshold is 0.8.
9. A video-stuck detection system, comprising an image capturing apparatus and a video-stuck detection device according to any one of claims 5 to 8;
the camera equipment is connected with the video clamping detection device;
the image pickup device is used for collecting image information of the target device in a detection time period.
10. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the steps of the video clip detection method according to any one of claims 1-4.
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