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http://dx.doi.org/10.5302/J.ICROS.2013.13.9038

Specific Material Detection with Similar Colors using Feature Selection and Band Ratio in Hyperspectral Image  

Shim, Min-Sheob (Department of Electronic Engineering, LED-IT Fusion Technology Research Center, Yeungnam University)
Kim, Sungho (Department of Electronic Engineering, LED-IT Fusion Technology Research Center, Yeungnam University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.12, 2013 , pp. 1081-1088 More about this Journal
Abstract
Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.
Keywords
hyperspectral imagery; feature selection; simulated annealing; band ratio; target detection; specific region detection;
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Times Cited By KSCI : 2  (Citation Analysis)
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