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

Liu, J. and Wei, H. ORCID: https://orcid.org/0000-0002-9664-5748 (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 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.