Infrared image target detection process using continuous features

Minoru Kikuchi; Hiroyuki Tamura; Michinari Ono; Hiroshi Miyauchi; Shigenobu Kobayashi

doi:10.1117/12.395593

17 August 2000 Infrared image target detection process using continuous features

Minoru Kikuchi, Hiroyuki Tamura, Michinari Ono, Hiroshi Miyauchi, Shigenobu Kobayashi

Proceedings Volume 4050, Automatic Target Recognition X; (2000) https://doi.org/10.1117/12.395593
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In this paper, we discuss stability and accuracy of target detection process in infrared images, using continuous features of the target or target candidates, and we improve the accuracy of target detection by optimizing an evaluation function. This process carries out parallel image process. The one, Two-dimensional Constant False Alarm Rate (CFAR) process reduces background clatter. The other, Motion Vector Process detects moving target. In addition, Combined Target Detection Process improves the accuracy of target detection using features from two different processes. Continuous and stable data measurement is necessary to improve the accuracy of target detection. But measurement data have noises and fluctuations by change of the environment. In this case, we use continuous features to stable detection. On the other hand, optimizing weight vectors in evaluation function is necessary to improve target detection. But we have to deal with large number of parameters. In this optimization named Combined Target Detection Process, we use Genetic Algorithms (GA) to get a global optimum of parameters. This process is useful for outdoor surveillance systems, intelligent transport systems (ITS) and so on.

Citation Download Citation

Minoru Kikuchi, Hiroyuki Tamura, Michinari Ono, Hiroshi Miyauchi, and Shigenobu Kobayashi "Infrared image target detection process using continuous features", Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000); https://doi.org/10.1117/12.395593

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