Sonar Image Classification Based on Directional Wavelet and Fuzzy Fractal Dimension

摘要：

This paper presents a supervised classification method of sonar image, which takes advantages of both directional wavelet (DW) and fuzzy fractal dimension (FFD). The definition of FFD is an extension of the pixel-covering method by incorporating the fuzzy set. DW is used for the decomposition of original images. In the process of feature extraction, a feature set is obtained by estimating the FFD of the directional wavelet transform sub-images. In the part of classifier construction, the learning vector quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification have been carried out with satisfactory results, which verify the effectiveness of this method.

作者: Yingli WANG Zhuofu LIU Enfang SANG Hongbin MA

作者单位: Department of Electrical Eenginerring,Department of Underwater Acoustic Eenginerring,Harbin Engineer Department of Underwater Acoustic Eenginerring,Harbin Engineering University, China Department of Underwater Acoustic Eenginerring,,Harbin Engineering University, China Department of Electrical Eenginerring,Heilongjiang University, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）