Wavelet Based Features for Defect Detection in Fabric using Genetic Algorithm

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 3

Abstract

 Abstract: In this paper a new scheme is proposed for Fabric defect detection in textile industry. For this purpose, wavelet transformer is used as feature extractor of coefficients of fabric. These coefficients can defect main fabric image & indicate defects of fabric textile by optimal subset of these coefficients. For finding a suitable subset Genetic Algorithm is used defect detector. The Shannon entropy is used as evaluation function in Genetic Algorithm. By using two separable sets of wavelet coefficients for horizontal and vertical defects, it was seen that we get better results for defect detection. The advantage of this approach it improves accuracy of fabric defect detection as well decrease computation time

Authors and Affiliations

Prajakta A. Jadhav , Prof. M. S. Biradar

Keywords

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  • EP ID EP99758
  • DOI 10.9790/0661-1633116120
  • Views 106
  • Downloads 0

How To Cite

Prajakta A. Jadhav, Prof. M. S. Biradar (2014).  Wavelet Based Features for Defect Detection in Fabric using Genetic Algorithm. IOSR Journals (IOSR Journal of Computer Engineering), 16(3), 116-120. https://europub.co.uk/articles/-A-99758