Abstract Conventional moving object detection methods are usually based on pixel or hard-divided-blocks. In this paper, watershed transformation is applied to segment an image into homogenous regions adaptively, and these regions are then used as minimal processing cell for moving object detection. To alleviate the over-segmentation problem, watershed transformation is performed on multi-stage morphological gradient image. To meet the requirement of low false alarm and high real-time performance, a homogenous region belonging to foreground or background is judged directly by measuring intensity difference, chromaticity distortion, and intensity relation among adjacent regions between the region and its corresponding regions in a series of maintained history background image. The false alarm of the proposed approach is lower than that of the popular detection methods, and it avoids the hard block-split problem in region-based detection approaches. The processing speed of the proposed approach is also satisfactory. Experiments on several benchmark video sequences are made including both indoor and outdoor scenes, and the results demonstrate the effectiveness of the proposed algorithm.
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2009, Vol. 22 
