CN110719474A - Monitoring video secondary compression method based on connected domain analysis - Google Patents
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Abstract
本发明公开一种基于连通域分析的监控视频二次压缩方法，涉及视频数据处理技术领域，获取待压缩监控视频，选取背景帧，检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩。
The invention discloses a monitoring video secondary compression method based on connected domain analysis, and relates to the technical field of video data processing. The monitoring video to be compressed is obtained, a background frame is selected, and the difference between the current frame and the background frame is detected as exceeding a set threshold, and it is considered that There are pixels of moving objects in the current frame, and the connected domain analysis is performed on the current frame after image morphological operations to mark the area where the moving object is located, save the area where the moving object is located as an image, and keep the corresponding frame number and position of the current frame. , the background frame and all frames with moving objects are packaged to complete the secondary compression of the surveillance video.
Description
技术领域technical field
本发明公开一种基于连通域分析的监控视频二次压缩方法，涉及视频数据处理技术领域。The invention discloses a monitoring video secondary compression method based on connected domain analysis, and relates to the technical field of video data processing.
背景技术Background technique
视频信息在互联网时代扮演着日渐重要的角色。随着监控设备的日渐普及，产生了海量的视频数据，长时间不间断的视频存储非常耗费存储空间，而大部分的监控视频数据通常包含的有效信息有限，但却占据了大量的存储空间，不利于视频的长期存储及使用。Video information plays an increasingly important role in the Internet age. With the increasing popularity of monitoring equipment, a large amount of video data is generated. Long-term uninterrupted video storage consumes a lot of storage space. Most of the monitoring video data usually contains limited effective information, but it occupies a large amount of storage space. It is not conducive to the long-term storage and use of the video.
本发明公开一种基于连通域分析的监控视频二次压缩方法，基于压缩不同帧间变化较少的像素，通过连通域分析，提取并保留变化的像素，从而达到二次压缩的目的。本发明同时运用了基于多帧图像融合的方法进行背景帧提取，可以在保证有效信息保留的情况下，减少视频数据的存储空间，并使用更复杂的目标检测进行优化提升的可能，可扩展性较强。The invention discloses a monitoring video secondary compression method based on connected domain analysis. Based on compressing pixels with less variation between different frames, the changed pixels are extracted and retained through the connected domain analysis, so as to achieve the purpose of secondary compression. The invention also uses the method based on multi-frame image fusion to extract background frames, which can reduce the storage space of video data under the condition of ensuring effective information retention, and use more complex target detection to optimize and improve the possibility of scalability. strong.
发明内容SUMMARY OF THE INVENTION
本发明针对现有技术的问题，提供一种基于连通域分析的监控视频二次压缩方法，可以在保证有效信息保留的情况下，减少视频数据的存储空间。Aiming at the problems of the prior art, the present invention provides a method for secondary compression of surveillance video based on connected domain analysis, which can reduce the storage space of video data under the condition of ensuring effective information retention.
本发明提出的具体方案是：The concrete scheme proposed by the present invention is:
一种基于连通域分析的监控视频二次压缩方法，获取待压缩监控视频，A surveillance video secondary compression method based on connected domain analysis, obtains surveillance video to be compressed,
选取背景帧，select background frame,
检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，If the difference between the current frame and the background frame exceeds the set threshold, it is considered that there are pixels of moving objects in the current frame, and the connected domain analysis is performed on the current frame after image morphological operations to mark the area where the moving objects are located.
将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，Save the area where the moving object is located as an image, while retaining the corresponding frame number and position of the current frame,
将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩。After packing the background frame and all frames with moving objects, the secondary compression of the surveillance video is completed.
所述的方法中选择一定时间内背景没有变化及视角不变的当前帧作为背景帧。In the method, a current frame with no change in the background and a constant viewing angle within a certain period of time is selected as the background frame.
所述的方法中一定时间内选取监控视频的多张当前帧的图像，将多张图像中没有改变的区域进行多图像融合，作为背景帧。In the method, a plurality of images of the current frame of the monitoring video are selected within a certain period of time, and the unchanged regions in the plurality of images are multi-image fusion as background frames.
所述的方法中使用最小矩形区域算法对运动物体所在区域进行标注。In the method, the minimum rectangle area algorithm is used to mark the area where the moving object is located.
一种基于连通域分析的监控视频二次压缩工具，包括采集模块、选取模块、检测模块及压缩模块，A monitoring video secondary compression tool based on connected domain analysis, comprising an acquisition module, a selection module, a detection module and a compression module,
采集模块获取待压缩监控视频，The acquisition module obtains the surveillance video to be compressed,
选取模块从监控视频中选取背景帧，The selection module selects the background frame from the surveillance video,
检测模块从监控视频中检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，The detection module detects from the surveillance video that the difference between the current frame and the background frame exceeds the set threshold, and considers that there are pixels of a moving object in the current frame, and performs a connected domain analysis on the current frame through image morphological operations to mark the area where the moving object is located. ,
压缩模块将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩。The compression module saves the area where the moving object is located in the form of an image, while retaining the frame number and position of the corresponding current frame, and packs the background frame and all frames with moving objects to complete the secondary compression of the surveillance video.
所述的工具中选取模块选择一定时间内背景没有变化及视角不变的当前帧作为背景帧。The selection module in the tool selects the current frame with no change in the background and constant viewing angle within a certain period of time as the background frame.
所述的工具中选取模块在一定时间内选取监控视频的多张当前帧的图像，将多张图像中没有改变的区域进行多图像融合，作为背景帧。The selection module in the tool selects a plurality of images of the current frame of the surveillance video within a certain period of time, and performs multi-image fusion on the unchanged regions in the plurality of images as background frames.
所述的工具中检测模块使用最小矩形区域算法对运动物体所在区域进行标注。The detection module in the tool uses the smallest rectangular area algorithm to mark the area where the moving object is located.
本发明的有益之处是：The benefits of the present invention are:
本发明提供一种基于连通域分析的监控视频二次压缩方法，获取待压缩监控视频，选取背景帧，检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩；The present invention provides a monitoring video secondary compression method based on connected domain analysis. The monitoring video to be compressed is obtained, a background frame is selected, and the difference between the current frame and the background frame is detected to exceed a set threshold, and the current frame is considered to have pixels of moving objects. , perform connected domain analysis on the current frame after image morphological operation, mark the area where the moving object is located, save the area where the moving object is located as an image form, and keep the corresponding frame number and position of the current frame, and compare the background frame and the existing motion After all the frames of the object are packaged, the secondary compression of the surveillance video is completed;
本发明方法基于压缩不同帧间变化较少的像素，通过连通域分析，提取并保留变化的像素，从而达到二次压缩的目的。本发明同时运用了基于多帧图像融合的方法进行背景帧提取，可以在保证有效信息保留的情况下，减少视频数据的存储空间，并使用更复杂的目标检测进行优化提升的可能，可扩展性较强。The method of the invention is based on compressing the pixels with less change between different frames, and extracts and retains the changed pixels through the analysis of the connected domain, so as to achieve the purpose of secondary compression. The invention also uses the method based on multi-frame image fusion to extract background frames, which can reduce the storage space of video data under the condition of ensuring effective information retention, and use more complex target detection to optimize and improve the possibility of scalability. strong.
附图说明Description of drawings
图1是本发明方法流程示意图。Fig. 1 is the schematic flow chart of the method of the present invention.
具体实施方式Detailed ways
本发明提供一种基于连通域分析的监控视频二次压缩方法，获取待压缩监控视频，The present invention provides a monitoring video secondary compression method based on connected domain analysis, and obtains the monitoring video to be compressed,
选取背景帧，select background frame,
检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，If the difference between the current frame and the background frame exceeds the set threshold, it is considered that there are pixels of moving objects in the current frame, and the connected domain analysis is performed on the current frame after image morphological operations to mark the area where the moving objects are located.
将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，Save the area where the moving object is located as an image, while retaining the corresponding frame number and position of the current frame,
将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩。After packing the background frame and all frames with moving objects, the secondary compression of the surveillance video is completed.
所述的方法中选择一定时间内背景没有变化及视角不变的当前帧作为背景帧。In the method, a current frame with no change in the background and a constant viewing angle within a certain period of time is selected as the background frame.
同时提供与上述方法相应的一种基于连通域分析的监控视频二次压缩工具，包括采集模块、选取模块、检测模块及压缩模块，At the same time, a monitoring video secondary compression tool based on connected domain analysis corresponding to the above method is provided, including a collection module, a selection module, a detection module and a compression module,
采集模块获取待压缩监控视频，The acquisition module obtains the surveillance video to be compressed,
选取模块从监控视频中选取背景帧，The selection module selects the background frame from the surveillance video,
检测模块从监控视频中检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作后进行连通域分析对运动物体所在区域进行标注，The detection module detects from the surveillance video that the difference between the current frame and the background frame exceeds the set threshold, and considers that there are pixels of a moving object in the current frame, and performs a connected domain analysis on the current frame through image morphological operations to mark the area where the moving object is located. ,
压缩模块将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置，将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩。The compression module saves the area where the moving object is located in the form of an image, while retaining the frame number and position of the corresponding current frame, and packs the background frame and all frames with moving objects to complete the secondary compression of the surveillance video.
下面结合附图和具体实施例对本发明作进一步说明，以使本领域的技术人员可以更好地理解本发明并能予以实施，但所举实施例不作为对本发明的限定。The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.
利用本发明方法基于连通域分析的监控视频进行二次压缩时，具体过程如下：When utilizing the method of the present invention to perform secondary compression on the surveillance video based on the connected domain analysis, the specific process is as follows:
S1：获取待压缩监控视频，并以帧为单位读取或直接保存，S1: Obtain the surveillance video to be compressed, and read it in frame units or save it directly.
S2：选取背景帧，可选择一定时间内背景没有变化及视角不变的当前帧作为背景帧，比如选定第一帧等等，S2: Select the background frame, select the current frame with no change in the background and the same viewing angle within a certain period of time as the background frame, such as selecting the first frame, etc.
或者一定时间内选取监控视频的多张当前帧的图像，将多张图像中没有改变的区域进行多图像融合，作为背景帧，Or select multiple images of the current frame of the surveillance video within a certain period of time, and perform multi-image fusion on the unchanged areas in the multiple images as background frames.
S3：当前帧与背景帧做差值，检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作进行膨胀后，进行连通域分析对运动物体所在区域使用最小矩形区域算法进行标注，S3: Make the difference between the current frame and the background frame. If the difference between the current frame and the background frame exceeds the set threshold, it is considered that there are pixels of moving objects in the current frame. After the current frame is expanded through image morphological operations, the connected domain is performed. The analysis uses the minimum rectangular area algorithm to mark the area where the moving object is located.
S4：将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置等信息，S4: Save the area where the moving object is located in the form of an image, while retaining the corresponding information such as the number of frames and the position of the current frame,
S5：将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩:背景帧和存在运动物体的所有帧打包后可作为中间文件进行传输，在接收端进行原视频的还复工作。S5: Pack the background frames and all frames with moving objects to complete the secondary compression of the surveillance video: After packing the background frames and all frames with moving objects, they can be transmitted as intermediate files, and the original video can be restored at the receiving end. .
上述方法中，S3也可利用深度学习中的目标检测如Faster RCNN、YOLO、SSD等算法进行运动物体像素的检测，保留运动目标和区域，同样可以减少计算量，优化准确率，提升视频压缩的效率和质量。Among the above methods, S3 can also use the target detection in deep learning such as Faster RCNN, YOLO, SSD and other algorithms to detect moving object pixels, and retain moving targets and regions, which can also reduce the amount of calculation, optimize the accuracy, and improve the performance of video compression. Efficiency and quality.
利用本发明工具基于连通域分析的监控视频进行二次压缩时，具体过程如下：When utilizing the tool of the present invention to perform secondary compression based on the monitoring video analyzed by the connected domain, the specific process is as follows:
S1：采集模块获取待压缩监控视频，并以帧为单位读取或直接保存，S1: The acquisition module obtains the surveillance video to be compressed, and reads it in frame units or saves it directly.
S2：选取模块选取背景帧，可选择一定时间内背景没有变化及视角不变的当前帧作为背景帧，比如选定第一帧等等，S2: The selection module selects the background frame, and the current frame with no change in the background and the same viewing angle within a certain period of time can be selected as the background frame, such as selecting the first frame, etc.,
或者一定时间内选取监控视频的多张当前帧的图像，将多张图像中没有改变的区域进行多图像融合，作为背景帧，Or select multiple images of the current frame of the surveillance video within a certain period of time, and perform multi-image fusion on the unchanged areas in the multiple images as background frames.
S3：检测模块将当前帧与背景帧做差值，检测当前帧与背景帧的差值超过设定的阈值则认为当前帧存在运动物体的像素，对当前帧通过图像形态学操作进行膨胀后，进行连通域分析对运动物体所在区域使用最小矩形区域算法进行标注，S3: The detection module makes the difference between the current frame and the background frame, and detects that the difference between the current frame and the background frame exceeds the set threshold, and considers that the current frame has pixels of moving objects, and after expanding the current frame through image morphological operations, Perform connected domain analysis to mark the area where the moving object is located using the minimum rectangular area algorithm.
S4：压缩模块将运动物体所在区域保存为图像形式，同时保留相应的当前帧的帧数和位置等信息，S4: The compression module saves the area where the moving object is located in the form of an image, and at the same time retains information such as the frame number and position of the corresponding current frame,
S5：压缩模块将背景帧和存在运动物体的所有帧打包后完成监控视频的二次压缩:背景帧和存在运动物体的所有帧打包后可作为中间文件进行传输，在接收端进行原视频的还复工作。S5: The compression module packages the background frames and all frames with moving objects to complete the secondary compression of the surveillance video: the background frames and all frames with moving objects can be packaged and transmitted as intermediate files, and the original video is restored at the receiving end. resume work.
上述工具中，S3中检测模块也可利用深度学习中的目标检测如Faster RCNN、YOLO、SSD等算法进行运动物体像素的检测，保留运动目标和区域，同样可以减少计算量，优化准确率，提升视频压缩的效率和质量。Among the above tools, the detection module in S3 can also use the target detection in deep learning such as Faster RCNN, YOLO, SSD and other algorithms to detect moving object pixels, keep moving targets and regions, and also reduce the amount of calculation, optimize the accuracy rate, improve Efficiency and quality of video compression.
本发明方法将背景帧视为一个冗余程度很大的信息，在没有感兴趣物体移动的情况下，对于一段视频压缩到一张图像的大小，因此在保证有效信息保留的情况下，减少视频数据的存储空间，保持视频的原始压缩率，并使用更复杂的目标检测进行优化提升还原视频的质量。The method of the present invention regards the background frame as a piece of information with a large degree of redundancy. In the case of no movement of the object of interest, a piece of video is compressed to the size of an image. Therefore, under the condition of ensuring the retention of effective information, the video is reduced. Data storage space, maintain the original compression rate of the video, and use more complex object detection for optimization to improve the quality of the restored video.
以上所述实施例仅是为充分说明本发明而所举的较佳的实施例，本发明的保护范围不限于此。本技术领域的技术人员在本发明基础上所作的等同替代或变换，均在本发明的保护范围之内。本发明的保护范围以权利要求书为准。The above-mentioned embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art on the basis of the present invention are all within the protection scope of the present invention. The protection scope of the present invention is subject to the claims.
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