An intelligent model for detecting and classifying color-textured fabric defects using genetic algorithms and the Elman neural network

In this paper, an intelligent color-textured fabric defect detection and classification model using genetic algorithms and the Elman neural network is introduced. A color ring projection is used for image processing, and the solution for optimization of parameters is based on the genetic algorithm m...

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Bibliographic Details
Published inTextile research journal Vol. 81; no. 17; pp. 1772 - 1787
Main Authors Zhang, YH, Yuen, CWM, Wong, WK, Kan, Chi-wai
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.10.2011
Sage Publications Ltd
Subjects
Classification
Color
Defects
Derivatives
Fabrics
Genetic algorithms
Mathematical models
Neural networks
Stitching
Studies
Textiles
genetic algorithm
fabric defect detection
color ring-projection classification
Elman neural network
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Summary:In this paper, an intelligent color-textured fabric defect detection and classification model using genetic algorithms and the Elman neural network is introduced. A color ring projection is used for image processing, and the solution for optimization of parameters is based on the genetic algorithm method. The new modified Elman network is proposed to classify the type of fabric defects, which have proportional, integral, and derivative properties. The proposed inspecting model in this study is more feasible and applicable in fabric and stitching garment defect detection and classification.
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ISSN:0040-5175
1746-7748
DOI:10.1177/0040517511410102