Robust multi-stage approach for the detection of moving target from infrared imagery

Bingwen Chen; Wenwei Wang; Qianqing Qin

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Robust multi-stage approach for the detection of moving target from infrared imagery

机译：Robust multi-stage approach for the detection of moving target from infrared imagery

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摘要

We present a multi-stage classification approach to detect targets in widely varying thermal imagery. A multi-level spatial-temporal median filter is utilized to extract the background frame, with which the background clutters are suppressed by using the principal component analysis technique. A spatially related fuzzy adaptive resonance theory (ART) neural network is then applied to identify the local regions-of-interest. Within each region, another fuzzy ART neural network is utilized to detect the targets. Experimental results demonstrate that the proposed approach is capable of detecting infrared moving targets effectively for F1 measurement up to 96.3percent.

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来源
《Optical Engineering》 |2012年第6期|067006-1-067006-9|共9页
作者
Bingwen Chen; Wenwei Wang; Qianqing Qin;
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作者单位

Wuhan University, School of Electronic Information, Wuhan 430079, China;

Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan 430079, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
multi-stage classification; multi-level spatial-temporal median filter; spatially related fuzzy adaptive resonance theory neural network; principal component analysis;

Robust multi-stage approach for the detection of moving target from infrared imagery

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