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14 December 2015 A long-term target detection approach in infrared image sequence
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Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 98120D (2015) https://doi.org/10.1117/12.2203718
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.
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Hang Li, Qi Zhang, Yuanyuan Li, and Liqiang Wang "A long-term target detection approach in infrared image sequence", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120D (14 December 2015); https://doi.org/10.1117/12.2203718
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