WAVELET BASED FEATURES FOR TEXTURE CLASSIFICATION

Abstract

This paper presents a feature extraction algorithm using wavelet decomposed images of an image and its complementary image for texture classification. The features are constructed from the different combination of sub-band images. These features offer a better discriminating strategy for texture classification and enhance the classification rate. In our study we have used the Euclidean distance measure and the minimum distance classifier to classify the texture. The experimental results demonstrate the efficiency of the proposed algorithm.