30 October 2009 Automatic detection of small moving targets in a five-ocular composite optical imaging system
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Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74952B (2009) https://doi.org/10.1117/12.833999
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
It is quite difficult to realize the automatic detection and determination of the small moving targets by the images data captured from a mono-aperture imaging system. Therefore a five-ocular composite optical imaging system is designed. The system is constituted by an infrared imaging system in the center and four visible imaging subsystems around the center subsystem. According to the inner feature of the overlapping field of view in the five-ocular composite optical imaging system, the automatic detection and recognition algorithm of the small moving targets for this system is built up. The algorithm is divided into four steps: the first step is preprocessing to get rid of low frequency background pixels, the second step is detecting the candidates of the small moving targets in the high frequency images remained by preprocessing, the third step is determining the true small moving targets from the candidates, and the last step is combining the detecting results of the visible subsystems into the detecting results of the infrared subsystem to determine the small moving targets are "live" or "dead", because the "dead" targets with lower temperature are not observed in the infrared subsystem. The test result in the experimental system indicated that the designed detection and recognition algorithm increased the detecting probability of the small moving targets, and decreased the probability of false alarms. The detection and recognition method was proved to be feasible and effective.
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You-Shan Qu, You-Shan Qu, Xue-Wu Fan, Xue-Wu Fan, } "Automatic detection of small moving targets in a five-ocular composite optical imaging system", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74952B (30 October 2009); doi: 10.1117/12.833999; https://doi.org/10.1117/12.833999
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