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Seafloor Classification Based on the Texture Analysis of Sonar Images Using the Gabor Wavelet
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  • Seafloor Classification Based on the Texture Analysis of Sonar Images Using the Gabor Wavelet
  • Seafloor Classification Based on the Texture Analysis of Sonar Images Using the Gabor Wavelet
저자명
Sun. Ning,Shim. Tae-Bo
간행물명
The journal of the Acoustical Society of Korea
권/호정보
2008년|27권 |pp.77-83 (7 pages)
발행정보
한국음향학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

In the process of the sonar image textures produced, the orientation and scale factors are very significant. However, most of the related methods ignore the directional information and scale invariance or just pay attention to one of them. To overcome this problem, we apply Gabor wavelet to extract the features of sonar images, which combine the advantages of both the Gabor filter and traditional wavelet function. The mother wavelet is designed with constrained parameters and the optimal parameters will be selected at each orientation, with the help of bandwidth parameters based on the Fisher criterion. The Gabor wavelet can have the properties of both multi-scale and multi-orientation. Based on our experiment, this method is more appropriate than traditional wavelet or single Gabor filter as it provides the better discrimination of the textures and improves the recognition rate effectively. Meanwhile, comparing with other fusion methods, it can reduce the complexity and improve the calculation efficiency.