Video signal problem frame detection method and device, equipment and storage medium

Abstract

The invention relates to a video signal problem frame detection method and device, equipment and a storage medium. The detection method comprises the following steps: acquiring at least one video stream and acquiring the video stream frame by frame; extracting behavior characteristics which suddenly appear in the video signal and reflect video dynamic characteristics; and analyzing the extracted behavior characteristics by using the trained model, judging whether the video frame accords with the characteristics of the problem frame, and if so, labeling the problem frame. The video signal problem frame detection method and device, the equipment and the storage medium are ingenious in design, whether the video frames conform to the features of the problem frames or not is judged by extracting the behavior features in the video frames and analyzing the behavior features, if yes, the suspected problem frames are labeled with the problem frames, the problem frames can be detected in real time in video stream processing, and the detection efficiency is improved. The post-processing is not needed, the abnormal frame possibly existing in the digital video signal stream is accurately identified, and the misjudgment caused by the static characteristic change of the frame content can be effectively avoided.

Description

Technical Field

[0001] The present invention relates to the field of video processing technology, and more specifically, to a method, device, equipment and storage medium for detecting problem frames of a video signal. Background Art

[0002] In digital video signal processing, various types of problem frames (such as frame loss, freeze, and screen distortion) may appear in the video signal due to various factors such as signal interference, coding loss, and transmission errors. These problems not only affect the smoothness and visual experience of the video content, but may also cause the loss of important information in certain scenarios, so it is necessary to detect the video frame signal.

[0003] Existing video frame detection methods mainly rely on static image comparison between frames, which is easily affected by image content and brightness. There is currently a lack of effective detection methods for behavioral features that suddenly appear in videos, such as motion blur, color shift, flicker, etc. Therefore, there is an urgent need for a detection system based on video behavior analysis that can detect and locate problem frames through dynamically changing behavioral features. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method, device, equipment and storage medium for detecting problem frames of video signals in view of the above-mentioned defects of the prior art, aiming to accurately detect abnormal frames that may exist in the digital video signal stream. By analyzing the video behavior characteristics between frames, a set of detection models is constructed, which can effectively capture and mark problem frames with frame loss, screen distortion, freeze, color distortion, etc.

[0005] On the one hand, the technical solution adopted by the present invention to solve its technical problem is: a method for detecting problematic frames of a video signal, wherein the detection method comprises the following steps:

[0006] Obtain at least one video stream and collect it frame by frame;

[0007] Extract behavioral features that suddenly appear in video signals and reflect the dynamic characteristics of the video;

[0008] The extracted behavioral features are analyzed using the trained model to determine whether the video frame meets the characteristics of the problem frame. If so, the suspected problem frame is labeled as a problem frame.

[0009] The detection method of the present invention, wherein, after the problem frame is detected, the detection result is stored in the form of a data report, and a report output in a variety of formats is provided.

[0010] In the detection method described in the present invention, the behavior characteristics include motion characteristics, color information, and texture changes between frames.

[0011] In the detection method described in the present invention, the problem frame is any type of frame loss, freeze, screen distortion, and color distortion.

[0012] In the detection method described in the present invention, when a sudden pause or misalignment of inter-frame motion features is detected, the problem frame is a stuck type problem frame.

[0013] In the detection method of the present invention, when it is detected that the amplitude and range of the color shift between frames exceeds or is less than a preset value range, the problem frame is a problem frame of the color distortion type.

[0014] On the other hand, the present invention also provides a device for detecting problem frames of a video signal, comprising:

[0015] The video frame acquisition module is used to obtain the video signal stream and collect it frame by frame;

[0016] A behavior feature extraction module is used to extract behavior features that suddenly appear in the video signal and reflect the dynamic characteristics of the video;

[0017] The problem frame detection module uses the trained model to analyze the extracted behavioral features, determine whether the video frame meets the characteristics of the problem frame, and label the suspected problem frame.

[0018] The detection device described in the present invention further includes a result feedback and recording module, which is used to store the detection results in the form of data reports and provide report outputs in multiple formats.

[0019] On the other hand, the present invention also provides a device, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the method for detecting problem frames of a video signal as described in any one of the above items.

[0020] On the other hand, the present invention further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for detecting problem frames of a video signal as described in any one of the above items are implemented.

[0021] The beneficial effects of the present invention are as follows: the detection method, device, equipment and storage medium of the problem frame of the video signal are cleverly designed. By extracting the behavioral features in the video frame and analyzing these behavioral features, it is determined whether the video frame meets the features of the problem frame. If so, the suspected problem frame is marked with a problem frame label. The problem frame can be detected in real time during video stream processing without the need for post-processing, and abnormal frames that may exist in the digital video signal stream can be accurately identified, which can effectively avoid misjudgments caused by changes in static features of the frame content. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work:

[0023] Figure 1 It is a principle flow chart of a method for detecting a problem frame of a video signal in Embodiment 1 of the present invention;

[0024] Figure 2 It is a schematic diagram of the principle of a device for detecting problematic frames of a video signal in Embodiment 2 of the present invention;

[0025] Figure 3 It is a structural block diagram of a device 30 in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0026] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present invention and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0027] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0028] "Multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0029] Moreover, the terms "up, down, front, back, left, right, upper end, lower end, longitudinal" and the like indicating directions are all based on the posture and position of the device or equipment described in this solution during normal use.

[0030] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the following will be described clearly and completely in combination with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are partial embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0031] 1. Embodiment 1:

[0032] A method for detecting problematic frames of a video signal in a preferred embodiment of the present invention is worthy of explanation. The present invention is applicable to video signals with different resolutions and frame rates, and can meet the detection requirements of various video scenes, such as Figure 1 As shown, the detection method comprises the following steps:

[0033] S10, obtaining at least one video stream and collecting it frame by frame; by collecting and analyzing it frame by frame, real-time monitoring of the video stream is achieved to ensure that problematic frames can be discovered in a timely manner.

[0034] S20, extracting behavioral features that suddenly appear in the video signal and reflect the dynamic characteristics of the video;

[0035] Because changes in behavioral features often indicate a decline in video quality, extracting these features can improve the sensitivity of the detection system to problem frames. By detecting sudden changes in the dynamic characteristics of the video, potential problems can be identified before the problem frames become obvious, thereby achieving early intervention. Changes in behavioral features in video signals often indicate a decline in video quality, so extracting these sudden abnormal changes in behavioral features can improve the sensitivity of the detection system to problem frames.

[0036] The behavior features include motion features, color information, and texture changes between frames. The detection method covers multiple dimensions such as motion features, color information, and texture changes, and can comprehensively evaluate the quality of video signals.

[0037] S30, using a trained model (such as a machine learning model) to analyze the extracted behavior features, determine whether the video frame meets the features of the problem frame, and if so, label the suspected problem frame with a problem frame label, thereby helping technicians to quickly locate the problem frame and take targeted solutions.

[0038] The problem frame is any one of frame loss, freeze, screen distortion, and color distortion.

[0039] For example, when a sudden pause or misalignment of inter-frame motion features is detected, the problem frame is a stuck type problem frame.

[0040] When it is detected that the amplitude and range of the color shift between frames exceeds or is less than a preset value range, the problem frame is a problem frame of the color distortion type.

[0041] S40, after the problem frame is detected, the detection result is stored in the form of a data report for subsequent analysis and tracing, and a variety of report output formats are provided to meet the needs of different users.

[0042] The detection method of problem frames in video signals is cleverly designed. It extracts behavioral features from video frames and analyzes these behavioral features to determine whether the video frames meet the features of problem frames. If so, the suspected problem frames are labeled as problem frames. It can detect problem frames in real time during video stream processing without the need for post-processing, and can accurately identify abnormal frames that may exist in the digital video signal stream, effectively avoiding misjudgments caused by changes in static features of frame content.

[0043] 2. Embodiment 2:

[0044] The present invention also provides a device for detecting problem frames of a video signal, such as Figure 2 As shown, it includes the following modules:

[0045] The video frame acquisition module 201 is used to acquire the video signal stream and acquire it frame by frame;

[0046] Behavior feature extraction module 202, used to extract behavior features that suddenly appear in the video signal and reflect the dynamic characteristics of the video;

[0047] The problem frame detection module 203 uses the trained model to analyze the extracted behavior features, determines whether the video frame meets the features of the problem frame, and labels the suspected problem frames.

[0048] Furthermore, the device also includes a result feedback and recording module 204, which is used to store the test results in the form of data reports and provide report outputs in multiple formats.

[0049] The detection device for problem frames in video signals is cleverly designed. It extracts behavioral features from video frames and analyzes these behavioral features to determine whether the video frames meet the features of problem frames. If so, the suspected problem frames are labeled as problem frames. It can detect problem frames in real time during video stream processing without the need for post-processing, and can accurately identify abnormal frames that may exist in the digital video signal stream, effectively avoiding misjudgments caused by changes in static features of frame content.

[0050] 3. Embodiment 3:

[0051] The present invention also provides a device 30, such as Figure 3As shown, it includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and capable of running on the processor 301. When the computer program 303 is executed by the processor 301, the steps of the video signal problem frame detection method as described in any one of the embodiments of the first embodiment are implemented.

[0052] 4. Embodiment 4

[0053] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for detecting problem frames of a video signal as described in any one of the first embodiments are implemented.

[0054] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all these improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A method for detecting problematic frames of a video signal, characterized in that: The detection method comprises the following steps: Obtain at least one video stream and collect it frame by frame; Extract behavioral features that suddenly appear in video signals and reflect the dynamic characteristics of the video; The extracted behavioral features are analyzed using the trained model to determine whether the video frame meets the characteristics of the problem frame. If so, the suspected problem frame is labeled as a problem frame.

2. The detection method according to claim 1, characterized in that: After the problem frame is detected, the detection result is stored in the form of a data report, and the report output is provided in multiple formats.

3. The detection method according to claim 1, characterized in that: The behavior features include motion features, color information, and texture changes between frames.

4. The detection method according to claim 1, characterized in that: The problem frame is any one of the following types: frame loss, freeze, screen distortion, and color distortion.

5. The detection method according to claim 4, characterized in that: When a sudden pause or misalignment of inter-frame motion features is detected, the problem frame is a stuck type problem frame.

6. The detection method according to claim 4, characterized in that: When it is detected that the amplitude and range of the color shift between frames exceeds or is less than a preset value range, the problem frame is a problem frame of the color distortion type.

7. A device for detecting problematic frames of a video signal, characterized in that: include: The video frame acquisition module is used to obtain the video signal stream and collect it frame by frame; A behavior feature extraction module is used to extract behavior features that suddenly appear in the video signal and reflect the dynamic characteristics of the video; The problem frame detection module uses the trained model to analyze the extracted behavioral features, determine whether the video frame meets the characteristics of the problem frame, and label the suspected problem frame.

8. The device according to claim 7, characterized in that It also includes a result feedback and recording module, which is used to store the test results in the form of data reports and provide report output in multiple formats.

9. A device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the method for detecting problem frames of a video signal as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for detecting problem frames of a video signal as described in any one of claims 1 to 6 are implemented.

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