Classification of Textures Based on Features Extracted from Preprocessing Images on Random Windows

Abstract

Textures are one of the important features in computer vision for many applications. In the literature, most of the attention has been focused on the texture features with minimal consideration of the noise models and window selection. To overcome this, in the present paper the features are constructed on preprocessed methods applied on the texture image by considering different types of windows. These features offer a better classification rate. The experimental results on various Brodatz textures clearly demonstrate the efficiency of the proposed method.