Chroma deviation and brightness deviation combined video moving object detection method
A moving target and chromaticity deviation technology, applied in the field of video processing, can solve the problems of poor background extraction and slow foreground movement, and achieve the effect of accurate moving target detection results.
Inactive Publication Date: 2008-01-02
SHANGHAI JIAO TONG UNIV
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The moving object detection method proposed by the present invention can solve the problem that the background extraction effect is not good when the number of video frames is small and the foreground movement is slow; some noise points are removed by median filtering of the luminance difference and chrominance difference matrix and Preserve the boundary; propose a method to determine the brightness difference threshold, which can accurately determine the corresponding brightness difference threshold according to the characteristics of different video sequences; preserve the boundary of the moving object through the projection of the point set, so that the detection result of the moving object is more accurate
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[0043]The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following the described embodiment.
[0044] As shown in FIG. 1 , this embodiment can be divided into the following steps.
[0045] (1) Using statistical methods to extract background frames in RGB channels
[0046] In the present embodiment, the background frame is extracted by dividing the RGB channel by using the method of statistics plus filtering, and the process flow is as shown in Figure 2, and the specific steps are as follows:
[0047] ① Use statistical method to extract background frame by RGB channel
[0048] The chromaticity value range of each channel of RGB is [0, 255]. Divide this interval...
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A video mobile target check method combining chromaticity bias and brightness bias, belonging to video processing technical field, comprises that first using statistic method to extract a background frame via different channels, then using middle-value filter to eliminate the interface of color imbalance point in the background frame, at last, replacing former RGB three-channel chromaticity value at saturation jump point into chromaticity average value of RGB three channels, before using brightness difference and chromaticity difference information to check foreground object, first filtering the brightness difference and chromaticity difference matrix, using static Gauss mode to calculate out the threshold value of the brightness difference, and finding the threshold value of the chromaticity difference according to experience value, at last, holding the boundary of checked result. The invention can accurately extract background frame without foreground information, under less video frames and slow foreground motion, which can accurately calculate out the brightness threshold value of foreground object according to the characters of different video sequences and store the boundary of mobile target, thereby accurately checking the mobile target in video sequence.
Description
technical field [0001] The invention relates to a video moving target detection method, in particular to a video moving target detection method combining chromaticity deviation and brightness deviation, and belongs to the technical field of video processing. Background technique [0002] Video moving object detection is to detect moving objects from video sequences, which is an important research content in computer vision, video image tracking and other application fields. Whether the moving target can be accurately and effectively detected and extracted directly affects the processing effect of subsequent target classification, tracking and behavior understanding. [0003] At present, the commonly used moving object detection methods include optical flow method, frame difference method and background difference method, and these three methods have their own advantages and disadvantages. Among them, the optical flow method has the most accurate detection results, but the c...
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IPC IPC(8): H04N7/18G06T7/20
Inventor 张瑞张思竹杨小康余松煜
Owner SHANGHAI JIAO TONG UNIV