Defect Detection and Identification in Textile Fabric by SVM Method

Abstract

In this paper we use a support vector machine (SVM) for defects identification in textile. This new approach serves in the fast detection and extraction of fabric defects from the images of textile fabric based on geometrical analysis of the textile pattern images. Actually, most defects arising in the production process of textile material are still detected by human inspection [1] and the work of inspectors is very tedious and time consuming. They have to detect small details that can be located; the identification rate is about 70%. In addition, the effectiveness of visual inspection decreases quickly with fatigue. For these reasons, an algorithm has been proposed for the defect identification and classification. So, the images analyzed came from an artificial vision system that we used to acquire and memorize those images under jpeg format. The vision system is composed of a camera with a sensor 512X512 Pixels. The classifier SVM was manipulated to classify all defects in the defected fabric.