Contourlet Detection and Feature Extraction for Automatic Target Recognition

被引：4
|
作者：
Wilbur, JoEllen [1 ]
McDonald, Robert J. [1 ]
Stack, Jason [2 ]
机构：
[1] NSWC PC, Code T13 Computat Sci, Panama City, FL 32407 USA
[2] ONR, Dept Engn & Marine Syst, Arlington, VA 22203 USA
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9 | 2009年
关键词：
contourlet; directional filterbank; kernel matching pursuit; relevance vector machine; support vector machince;
D O I：
10.1109/ICSMC.2009.5346564
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This research presents a contourlet based detection and feature extraction method for underwater targets. The method operates on Side Scan Sonar (SSS) images and is designed to automatically detect and generate target features for classification. Kernel based classifiers are used to determine the best boundary for separating targets and clutter. A statistically significant target data set is generated by embedding additional synthetic targets into SSS data collected during sea tests. Feature trade off studies show an improvement in classification results with the addition of directional based features.
引用
收藏
页码：2734 / +
页数：2
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