期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：11
页码：71
出版社：SERSC
摘要：This paper presents a non-stationary object detection methodby exploringtime-varying spatial domain informationin full motion video.Initially, the edge maps of difference image between two adjacent framesand current frameisgeneratedvia the well-known Canny edge detector. The distance of the edge pixelsbetween the difference imageand the current video frameare confinedwithin a small value to determine the initial edge mask for the object in motion. The horizontal and vertical filling followed by morphological opening and closing operator are applied onthe initial edge mask to create initial temporal segmentation mask of the moving object. Themorphological dilationand corrosion operatorare utilized to obtain binary marker image of the foreground and backgroundwhich are used to modify the multi-scale morphological gradient image of current frame.Finally, the watershed algorithm is performed on the modified gradients to find the non-stationary objects accurately in the spatial domain of motion frames. Processed video results show detection accuracy of 98% and 99% for fourdifferent video experimentation test-beds involving fast and slowhuman motion. In this operation, the proposed technique eliminates the problem of over-segmentation of the watershed algorithm and extracts visually distinct, contextually meaningfulnon-stationary objects as they randomly appear(or disappear)in video sequences
