A new intelligent fabric defect detection and classification system based on Gabor filter and modified Elman neural network

Y. H. Zhang, C. W.M. Yuen, Wai Keung Wong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

In this paper, one fabric defect detection and classification system based on 2D Gabor wavelet transform and Elman neural network is introduced. In the proposed scheme, the texture features of the textile fabric are extracted by using an optimal 2D Gabor filter. A new modified Elman network is proposed to classify the type of fabric defects which have a proportional (P), integral (I) and derivative (D) properties. The proposed inspecting system in this study is more feasible and applicable in fabric defect detection and classification.
Original languageEnglish
Title of host publicationProceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010
Pages652-656
Number of pages5
Volume2
DOIs
Publication statusPublished - 21 Oct 2010
Event2010 IEEE International Conference on Advanced Computer Control, ICACC 2010 -
Duration: 27 Mar 201029 Mar 2010

Conference

Conference2010 IEEE International Conference on Advanced Computer Control, ICACC 2010
Period27/03/1029/03/10

Keywords

  • Classification
  • Elman neural networ
  • Fabric defect detection
  • Gabor filter
  • PID

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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