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

Min-Sheob Shim; Sungho Kim

doi:10.1117/12.2015755

18 May 2013 Concealed target detection using hyperspectral imagers based on intersection kernel of SVM

Min-Sheob Shim, Sungho Kim

Proceedings Volume 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX; 874325 (2013) https://doi.org/10.1117/12.2015755
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Min-Sheob Shim and Sungho Kim "Concealed target detection using hyperspectral imagers based on intersection kernel of SVM", Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 874325 (18 May 2013); https://doi.org/10.1117/12.2015755

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available