REAL-TIME DETECTION OF KNITTING FABRIC DEFECTS USING SHEARLET TRANSFORM

Authors : Kazim Hanbay, Muhammed Fatih Talu, Ömer Faruk Özgüven, Dursun Öztürk

Pages : 1-10

Doi:10.32710/tekstilvekonfeksiyon.482888

View : 27 | Download : 9

Publication Date : 2019-03-26

Article Type : Research

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.
Keywords : Fabric defect detection, real-time inspection, texture classification