Texture classification of fabric defects using machine learning

Yassine Ben Salem (University of Gabes)
Mohamed Naceur Abdelkrim (University of Gabes)

International Journal of Electrical and Computer Engineering
Vol 10, No 4: August 2020

In this paper, a novel algorithm for automatic fabric defect classification was proposed, based on the combination of a texture analysis method and a support vector machine SVM. Three texture methods were used and compared, GLCM, LBP, and LPQ. They were combined with SVM’s classifier. The system has been tested using TILDA database. A comparative study of the performance and the running time of the three methods was carried out. The obtained results are interesting and show that LBP is the best method for recognition and classification and it proves that the SVM is a suitable classifier for such problems. We demonstrate that some defects are easier to classify than others.