Abstract
The detection of moving object is one of the key techniques for video surveillance. In order to extract the moving object robustly in complex background, this paper presents a novel background subtraction method for detecting foreground objects in dynamic scenes. The difference image of color distance between current image and the reference background image in YUV color space is first obtained. According to the mono-modal feature of histogram of the difference image, an adaptive clustering method based on histogram is given. With morphological filtering, the flecks of noise existed in the segmented binary image can be removed. Finally, an updating scheme for background image is introduced to follow the variation of illumination and environmental conditions. Experimental results show that the proposed approach can detect moving objects effectively from video sequences.
Highlights
The detecting of moving target in video sequence is of importance in many applications, such as intelligent transportation, safety monitoring, etc
The latter using the adjacent frame difference can extract information of moving objects, The method is robust to the change of environment, since it assumes that there should be a certain degree of difference of moving speed between target and background, and the information of grey scale or gradient of temporal difference image can be employed to obtain the moving information from the deviation of two or three consecutive frames. but objects of sudden stopping cannot be detected, and this method can not solve the problem of background exposed and the overlapping of moving objects in the adjacent frames
The experimental results shows that the method can segment moving object accurately and quickly
Summary
The detecting of moving target in video sequence is of importance in many applications, such as intelligent transportation, safety monitoring, etc. The impact of noise, many light source, shadows (Y.M.Wu, 2002, Wren, C.1997), transparency and shelter reduces the reliability and accuracy of the algorithm which is based on optical flow technology for moving object detection methods. Despite these difficulties, computational complexity and time-consuming further complicate the moving object detection in real-time monitoring(Lipton, A,1998), it is hard to meet real-time requirement without the support of specific hardware devices. Image difference method was divided into the background difference method and the inter-frame difference method The former algorithm is simple but it lacks a reasonable method for the background update, which changes with illumination and other factors. The current difference method, which didn’t make full use of rich color information, is generally limited to two images of the brightness, but color information is indispensable in practical application
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