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Integrating features for man-made target tracking from FLIR image sequence using particle filter

Liu, J. and Wei, H. (2010) Integrating features for man-made target tracking from FLIR image sequence using particle filter. In: 2010 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IET, pp. 484-488. ISBN 9781424450015

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To link to this item DOI: 10.1109/ICMTMA.2010.87

Abstract/Summary

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:17378
Additional Information:The conference was held in Changsha City, China, 13-14 March 2010.
Publisher:IET

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