8 December 2011 Fusion of multi-measures in infrared target recognition based on Dempster-Shafer evidence theory
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Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 80030H (2011) https://doi.org/10.1117/12.900304
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
The accuracy of target acquisition depends on preparation of templates and selection of matching measures. Consequently, the fusion of different information supplied by various metrics has important value to increase the success rate of target acquisition. The fusion of two measures is described to illustrate this method. We may firstly use template matching in terms of the first measure to find the locations and heights of top N peaks, and then compute the value under the other measure on the position of each peak. Regarding all of the peaks as the recognition frame and measures as different evidence, Dempster Combination Rules can be used to fuse the data. Furthermore, dual measures fusion can be extended to application of multiple measures. When more than two measures are employed, weights of different measures are unnecessary to be assigned artificially but gain from the distances between every two pieces of evidence. Some typical targets of urban tall buildings are used to test the performance of template matching with measures fusion. The experimental data validates the fusion of multi-measures is effective to improve the capability of target recognition.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tian Tian, Tian Tian, Delie Ming, Delie Ming, } "Fusion of multi-measures in infrared target recognition based on Dempster-Shafer evidence theory", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030H (8 December 2011); doi: 10.1117/12.900304; https://doi.org/10.1117/12.900304
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