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  • 标题:Texture classification of fabric defects using machine learning
  • 本地全文:下载
  • 作者:Yassine Ben Salem ; Mohamed Naceur Abdelkrim
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2020
  • 卷号:10
  • 期号:4
  • 页码:4390-4399
  • DOI:10.11591/ijece.v10i4.pp4390-4399
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要: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.
  • 关键词:texture classification;image processing;woven fabric defects;GLCM;LBP;LVQ;SVM classifier
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