张 刚1,2, 马宗民1(1.东北大学信息科学与工程学院, 沈阳 110004;2.沈阳工业大学软件学院, 沈阳 110023)
An Approach of Using Gabor Wavelets for Texture Feature Extraction
ZHANG Gang,1,2, MA Zongmin1(1.College of Information Science and Engineering, Northeastern University, Shenyang 110004;2.School of Software, Shenyang University of Technology, Shenyang 110023)
Gabor wavelets are one of the important approaches to texture feature extraction. Through the orthogonality of its base functions, the Gabor wavelets can not only extract texture features effectively, but also reduce redundancy. However, the texture feature vector computed from the Gabor wavelets has higher dimension. An approach using modified Gabor wavelets is presented in the paper. The approach uses the Gabor wavelets to compute energy of different scales and different directions, and the dominant peak set. Then the texture feature vector is computed from the dominant peak set. Furthermore, standardized energy is introduced into similarity measure as weights. Experiments show that the system that uses the modified Gabor wavelets has about the same retrieval performance as that uses the Gabor wavelets. However, the dimension of the texture feature vector of the former is only 6.1% of that of the latter.