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Proceedings Paper

Target Classification Algorithms For Video And Forward Looking Infrared (FLIR) Imagery
Author(s): Barbara H. Yin; Harold Mack
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Paper Abstract

The purpose of the target classification algorithms is to properly categorize the object isolated by the target detection and extraction algorithms. Feature determination and object classification with the given features are the two distinct phases associated with target classification. This paper compares the impact of using "radial and angular moments" versus Hu's seven Cartesian moment invariants, and also compares silhouette moments and intensity moments for feature extraction. The k-nearest neighbor approach is then used for the object classification phase. The efficacy of the technique has been evaluated off-line via the method of confusion matrices. The theoretical results are presented, supported by validation on the synthetic data base generated in our Digital Image Processing Lab.

Paper Details

Date Published: 8 March 1982
PDF: 8 pages
Proc. SPIE 0302, Infrared Technology for Target Detection and Classification, (8 March 1982); doi: 10.1117/12.932641
Show Author Affiliations
Barbara H. Yin, Ford Aerospace and Communications Corporation (United States)
Harold Mack, Ford Aerospace and Communications Corporation (United States)

Published in SPIE Proceedings Vol. 0302:
Infrared Technology for Target Detection and Classification
Pat M. Narendra, Editor(s)

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