Open Access

Survey on Various Defect Detection and Classification Methods in Fabric Images

M. Fathu Nisha,
Department of ECE, K. L. N. College of Information Technology, Madurai, TN, India. P. Vasuki, Department of ECE, K. L. N. College of Information Technology, Madurai, TN, India. S. Mohamed Monsoor Roomi

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Abstract

Fabric defect detection is a necessary and essential step of quality control in the textile manufacturing industry. This paper has been reviewed the various fabric defect detection and classification methods of statistical, spectral, model based and structural approaches. This paper has been presented the survey on types of defects, detection accuracy, performance metric and inference from recent publications. It will benefit researchers and practitioners in image processing and computer vision fields in understanding the characteristics of the different defect detection approaches. It concludes that the pulse coupled neural network (PCNN) approach is better detection accuracy than the other methods and is suggested for further research.

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