IJMTES -FABRIC DEFECT DETECTION USING FISHER CRITERION BASED AUTO ENCODER

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : FABRIC DEFECT DETECTION USING FISHER CRITERION BASED AUTO ENCODER

Author’s Name : Anitaa U | Dr Mariapriscillaunnamed

Volume 04 Issue 02 2017

ISSN no:  2348-3121

Page no: 75-78

Abstract – In textile industry production, automatic fabric inspection is important for maintain the fabric quality. For a long time the fabric defects inspection process is still carried out with human visual inspection, and thus, insufficient and costly. Therefore, automatic fabric defect inspection is required to reduce the cost and time waste caused by defects. The development of fully automated web inspection system requires robust and efficient fabric defect detection algorithms. In this paper we propose a Fisher Criterion Based Stacked Denoising Auto encoder for defect detection. The first method is divide the fabric patches according to weight of both defective and defect less patches. Then fabrics are classified into defected and defect less. Finally the defected part of the fabric region is segmented through proposed fuzzy c means segmentation.

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