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Proceedings Paper

Infrared image target detection process using continuous features
Author(s): Minoru Kikuchi; Hiroyuki Tamura; Michinari Ono; Hiroshi Miyauchi; Shigenobu Kobayashi
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Paper 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.

Paper Details

Date Published: 17 August 2000
PDF: 11 pages
Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000); doi: 10.1117/12.395593
Show Author Affiliations
Minoru Kikuchi, Toshiba Corp. (Japan)
Hiroyuki Tamura, Toshiba Corp. (Japan)
Michinari Ono, Toshiba Corp. (Japan)
Hiroshi Miyauchi, Toshiba Corp. (Japan)
Shigenobu Kobayashi, Tokyo Institute of Technology (Japan)

Published in SPIE Proceedings Vol. 4050:
Automatic Target Recognition X
Firooz A. Sadjadi, Editor(s)

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