Sea mine detection with a nearest-neighbor classifier based on residual vector quantization

Christopher F. Barnes

doi:10.1117/12.241219

31 May 1996 Sea mine detection with a nearest-neighbor classifier based on residual vector quantization

Christopher F. Barnes

Proceedings Volume 2765, Detection and Remediation Technologies for Mines and Minelike Targets; (1996) https://doi.org/10.1117/12.241219
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

The feasibility of using residual (multiple stage) vector quantizer codevectors in a nearest neighbor classifier for direct classification of sonar pixel data is established. This approach combines the successive approximation process generated by the residual vector quantizer with successive decision making. Experimental results show that the probability of detection is about 80% and that the false alarm rate if about 5.6 false alarms per image. These initial performance benchmarks are encouraging considering the heuristic manner in which the residual vector quantizer codebooks were employed in the nearest neighbor classifier.

Citation Download Citation

Christopher F. Barnes "Sea mine detection with a nearest-neighbor classifier based on residual vector quantization", Proc. SPIE 2765, Detection and Remediation Technologies for Mines and Minelike Targets, (31 May 1996); https://doi.org/10.1117/12.241219

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