Fusion of multi-measures in infrared target recognition based on Dempster-Shafer evidence theory
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.
Infrared target recognition Template matching DS Evidence Theory Multi-measures fusion
Tian Tian Delie Ming Feiran Jie Bo Lei
Institute of Pattern Recognition and Artificial Intelligence, Huazhong Univ. of Sci.& Tech., 1037Luo Institute of Pattern Recognition and Artificial Intelligence, Huazhong Univ. of Sci.& Tech., 1037Luo Sci. & Tech. on Electro-optic Control Laboratory, 25 Kaixuan west Road, Luoyang, Henan,P.R.China 471 Sci. & Tech. on Electro-optic Control Laboratory, 25 Kaixuan west Road, Luoyang, Henan, P.R.China 47
国际会议
桂林
英文
1-8
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）