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Automatic Target Recognition by selecting similarity-transform-invariant local and global features  

Sun, Sun-Gu (Department o Electrical Engineering and Computer Science, Division of Elcetrical Engineering, Korea Advanced Institute of Science and Technology)
Park, Hyun-Wook (Department o Electrical Engineering and Computer Science, Division of Elcetrical Engineering, Korea Advanced Institute of Science and Technology)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.39, no.4, 2002 , pp. 370-380 More about this Journal
Abstract
This paper proposes an ATR (Automatic Target Recognition) algorithm for identifying non-occluded and occluded military vehicles in natural FLIR (Forward Looking InfraRed) images. After segmenting a target, a radial function is defined from the target boundary to extract global shape features. Also, to extract local shape features of upper region of a target, a distance function is defined from boundary points and a line between two extreme points. From two functions and target contour, four global and four local shape features are proposed. They are much more invariant to translation, rotation and scale transform than traditional feature sets. In the experiments, we show that the proposed feature set is superior to the traditional feature sets with respect to the similarity-transform invariance and recognition performance.
Keywords
Automatic target recognition; Forward-looking infrared image; Feature extraction; Classification;
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Times Cited By KSCI : 1  (Citation Analysis)
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