Feature extraction and classification of woven fabric using optimized Haralick parameters: A rough set based approach

Classification of fabric samples into classes is highly required for automatic fabric inspection systems, as many of the fabric defects are defined relative to the fabric classes. The texture of the fabric surface is the best way to represent a fabric class, corresponding to which the statistical measures are the Haralick parameters. As all of the Haralick parameters are not responsible for fabric classification and there are no universal Haralick parameters for classifying all types of fabric samples, so it is necessary to determine a subset of Haralick parameters that gives best classification result for the fabric classes under consideration. This subset of Haralick parameters is termed as optimized Haralick parameters of the fabric classes under consideration, which has been determined by using the rough set theory. The developed system has been tested on TILDA database and its superiority with respect to the non-optimized Haralick parameters is established in terms of classification result and separability index.