An approach to infrared dim target detection and tracking

Authors:
Shi Liang;Bendu Bai;Ying Li
Affiliations:
School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China;School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China;School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China
Venue:
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2011

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Abstract

This paper presents a novel algorithm for detecting and tracking dim targets in infrared (IR) image sequence. Firstly the variance weighted information entropy (variance WIE) is introduced for the target detection after background suppression. The position and the size of the detected targets are then obtained to initialize the tracking algorithm. Then we adopt the local binary pattern (LBP) scheme to represent the target texture feature and propose a joint gray-texture histogram method for a more distinctive and effective target representation. Finally, target tracking is accomplished by using the mean shift algorithm. Experimental results indicate that the proposed method can effectively detect the dim targets and achieves much better tracking results compared with the traditional gray histogram based mean shift tracking.