A Multiresolution Approach for Noised Texture Classification based on the Co-occurrence Matrix and First Order Statistics

Authors: M. Ben Othmen, M. Sayadi, F. Fnaiech

Abstract:

Wavelet transform provides several important characteristics which can be used in a texture analysis and classification. In this work, an efficient texture classification method, which combines concepts from wavelet and co-occurrence matrices, is presented. An Euclidian distance classifier is used to evaluate the various methods of classification. A comparative study is essential to determine the ideal method. Using this conjecture, we developed a novel feature set for texture classification and demonstrate its effectiveness

Keywords: Classification, Wavelet, Co-occurrence, Euclidian Distance, Classifier, Texture.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1059561

References:

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