Identification of Defects in Textiles Based on Statistical Analysis of DCT Coefficients of Textile Images

This paper presents a novel approach to the fast detection and extraction of fabric defects from the images of textile fabric based on statistical analysis of the dct coefficients of the textile pattern images. Most defects arising in the production process of a textile material are still detected by human inspection. The work of inspectors is very tedious and time consuming. They have to detect small details that can be located in a wide area that is moving through their visual field. The identification rate is about 70%. In addition, the effectiveness of visual inspection decreases quickly with fatigue. However, the inspection process could be automated with machine vision techniques supported by defect identification algorithm. An image processing based machine vision system for visual inspection of fabric quality determination is proposed in the p[resented thesis work.