Sub image based eigen fabrics method using multi-class SVM classifier for the detection and classification of defects in woven fabric

Human visual system can identify larger defects taking place on the woven fabric. But it is very difficult to classify and identify the small fabric defects by a human inspector. In the textile industries the defect detection by a human inspector affects the production tremendously. Thus this paper gives a solution of this problem by developing an automatic fabric defect detection system, based on the computer vision. The sub image based PCA method is applied for the extraction of the feature from the training and test fabric images and the multi-class SVM classifier is used for carrying out the classification task. The method is tested on the standard TILDA database of fabric defect and a success rate of 96.36% is achieved.