Volume 18, No. 6, 2021

Fabric Defect Classification Using Ai Techniques

V.L Agrawal


In this paper a new classification algorithm is proposed for the Fabric Defect. In order to develop algorithm 164 different fabric images With a view to extract features from the images after image processing, analgorithm proposes (WHT)Wavelet Transform coefficients. The Efficient classifiers based on Modular neural Network (MNN). A separate Cross-Validation dataset is used for proper evaluation of the proposed classification algorithm with respect to important performance measures, such as MSE and classification accuracy. The Average Classification Accuracy of MNN Neural Network comprising of one hidden layers1 with 8 PEs organized in a typical topology is found to be superior (92.65 %) for Training. Finally, optimal algorithm has been developed on the basisof the best classifier performance. The algorithm will provide an effective alternative to traditional method of fabric defect analysis for deciding the best quality fabric.

Pages: 9012-9022

Keywords: Fabric defects, Neuro Solution Software, Microsoft excel, WHT Transform Techniques.

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