Abstract
This paper proposes a vision-based
 fabric inspection system for the circular knitting machine. Firstly, a
 comprehensive fabric database called Fabric Defect Detection Database (FDDD) are
 constructed. To extract significant features of fabric images, shearlet
 transform is used. Means and variances are calculated from all subbands and
 combined into a high-dimensional feature vector. The proposed system is evaluated
 on a circular knitting machine in a textile factory. The real-time performance
 analysis is only carried out by inspecting single jersey knitted fabric. Our
 proposed system achieves the highest accuracy of 94.0% in the detection of single
 jersey knitting fabric defects.
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