Texture classification of fabric defects using machine learning
2020 ◽
Vol 10
(4)
◽
pp. 4390
Keyword(s):
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.
2012 ◽
Vol 468-471
◽
pp. 2916-2919
2021 ◽
2020 ◽
Keyword(s):
2021 ◽
Vol 9
(B)
◽
pp. 1283-1289
2019 ◽
Vol 9
(3)
◽
pp. 66-69