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http://dx.doi.org/10.9708/jksci.2014.19.10.043

Gunnery Classification Method Using Profile Feature Extraction in Infrared Images  

Kim, Jae-Hyup (Samsung Thales Co.)
Cho, Tae-Wook (Samsung Thales Co.)
Chun, Seung-Woo (Samsung Thales Co.)
Lee, Jong-Min (Dept. of CSE, Hanyang University)
Moon, Young-Shik (Dept. of CSE, Hanyang University)
Publication Information
Journal of the Korea Society of Computer and Information / v.19, no.10, 2014 , pp. 43-53 More about this Journal
Abstract
Gunnery has been used to detect and classify artilleries. In this paper, we used electro-optical data to get the information of muzzle flash from the artilleries. Feature based approach was applied; we first defined features and sub-features. The number of sub-features was 38~40 generic sub-features, and 2 model-based sub-features. To classify multiclass data, we introduced tree structure with clustering the classes according to the similarity of them. SVM was used for each non-leaf nodes in the tree, as a sub-classifier. From the data, we extracted features and sub-features and classified them by the tree structure SVM classifier. The results showed that the performance of our classifier was good for our muzzle flash classification problem.
Keywords
Gunnery Classification; Tree Structure; SVM(Support Vector Machine);
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
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