Target Classification Algorithms For Video And Forward Looking Infrared (FLIR) Imagery

Barbara H. Yin; Harold Mack II

doi:10.1117/12.932641

8 March 1982 Target Classification Algorithms For Video And Forward Looking Infrared (FLIR) Imagery

Barbara H. Yin, Harold Mack II

Proceedings Volume 0302, Infrared Technology for Target Detection and Classification; (1982) https://doi.org/10.1117/12.932641
Event: 25th Annual Technical Symposium, 1981, San Diego, United States

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.

Citation Download Citation

Barbara H. Yin and Harold Mack II "Target Classification Algorithms For Video And Forward Looking Infrared (FLIR) Imagery", Proc. SPIE 0302, Infrared Technology for Target Detection and Classification, (8 March 1982); https://doi.org/10.1117/12.932641

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