Regular Paper

[OPTICAL REVIEW Vol. 21, No. 1 (2014) 27-34]
© 2014 The Japan Society of Applied Physics

A Method for Moving Objects Segmentation Based on Human Vision Perception in Infrared Video

Bin SUN1, Chaobo MIN1*, Junju ZHANG1, Bengkang CHANG1, Yingjie LI1, and Han YIYONG2

1School of Electronic Engineering and Optic-electronic Technology, Nanjing University of Science and Technology, Nanjing 210094, P. R. China
2Department of Electrical Engineering and Information Technology, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany

(Received October 23, 2013; Accepted November 20, 2013)

In this paper, a new region growing method to achieve the accurate and complete segmentation of the moving objects is introduced. Firstly, the ideal seeds of every moving object are extracted based on “hole” effect of temporal difference. Secondly, on the basis of the consideration that human vision system 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 moving objects. 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 infrared moving object.

Key words: image segmentation, spatial-temporal segmentation, human vision, infrared video

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