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.
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© 2012 Springer-Verlag Berlin Heidelberg
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Liang, S., Bai, B., Li, Y. (2012). An Approach to Infrared Dim Target Detection and Tracking. In: Zhang, Y., Zhou, ZH., Zhang, C., Li, Y. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2011. Lecture Notes in Computer Science, vol 7202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31919-8_33
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DOI: https://doi.org/10.1007/978-3-642-31919-8_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31918-1
Online ISBN: 978-3-642-31919-8
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