Optimal Approach for Texture Analysis and Classification based on Wavelet Transform and Neural Network

our aim in this work is to achieve an optimal approach of textures analysis and classification by combining Wavelet Transform and Neural Network. To reach a suitable way for textures recognition we first use Wavelet Transform to decompose texture into sub-images which are in turn analysed and finally features are extracted. The Neural Network uses the extracted features to classify the different types of textures. In this paper, we have analysed five types of textures and for each five different pictures have been used. We have obtained more accurate results.