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Proceedings Paper

Concealed target detection using hyperspectral imagers based on intersection kernel of SVM
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Paper Abstract

This paper presents a concealed target detection based on the intersection kernel Support Vector Machine (SVM). Hyperspectral imagers are widely used in the field of target detection and material analysis. In military applications, it can be used to border protection, concealed target detection, reconnaissance and surveillance. If disguised enemies not detected in advance, the damage of allies will be catastrophic by unexpected attack. Concealed object detection using radar and terahertz method is widely used. However, these active techniques are easily exposed to the enemy. Electronic Optical Counter Counter Measures (EOCCM) using hyperspectral imagers can be a feasible solution. We use the band selected feature directly and the intersection kernel based SVM. Different materials show different spectrums although they look similar in CCD camera. We propose novel concealed target detection method that consist of 4 step, Feature band selection, Feature Extraction, SVM learning and target detection.

Paper Details

Date Published: 18 May 2013
PDF: 10 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 874325 (18 May 2013); doi: 10.1117/12.2015755
Show Author Affiliations
Min-Sheob Shim, Yeungnam Univ. (Korea, Republic of)
Sungho Kim, Yeungnam Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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