New method for moving objects segmentation based on human vision perception in infrared video

摘要

A new method for moving object segmentation based on human vision perception in infrared video is proposed. In this paper, we introduce a new region growing method to achieve the accurate and complete segmentation of the moving objects. At first, the ideal seeds of every moving object are extracted based on the "hole" effect of temporal difference, respectively. At the next step, on the basis of the consideration that human vision system (HVS) is most sensitive to the local contrast between targets and surrounding, we proposed a metric for "good" infrared target segmentation based on human vision perception. And according to this metric, a search method based on fine and rough adjustment is applied to determine the best growing threshold for every moving object. The segmented mask of every moving object is grown from the relevant seeds with the best growing threshold. At last, the segmented masks of all moving objects are merged into a complete segmented mask. Experimental results show that the proposed method is superior and effective on segmentation of moving object in infrared video.