JOURNAL OF TEXTILE RESEARCH ›› 2011, Vol. 32 ›› Issue (9): 29-33.

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Fabric Defect Clustering Analysis based on Artificial Neural Network

  

  • Received:2010-09-06 Revised:2011-02-16 Online:2011-09-15 Published:2011-09-15

Abstract: It proposes a method to classify fabric defects based on artificial neural network in this paper. Firstly, gray co-occurrence matrix is used to extract texture feature parameters from fabric defects image. Then, the topology structure of forward feedback BP neural network is narrated, and also indicated the training process in detail. Finally, the BP artificial neural network is applied to fabric defects classification, the five kinds of fabric sample is used in the experiment, and defects data for classification can be gotten through neural network training process, these data can be used to classify fabric defects, the accuracy of classification is up to 100 percent, which verify the feasibility of the method mentioned in the paper.

CLC Number: 

  • TP311.131
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