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Automated defect detection in uniform and structured fabrics using Gabor filters and PCA
| Publication type | Journal paper |
|---|---|
| Year of publication | 2013 |
| Authors | Lucia Bissi, Giuseppe Baruffa, Pisana Placidi, Elisa Ricci, Andrea Scorzoni, and Paolo Valigi |
| Title | Automated defect detection in uniform and structured fabrics using Gabor filters and PCA |
| Journal title | Journal of Visual Communication and Image Representation |
| Volume | 24 |
| Issue | 7 |
| Pages | 838–845 |
| Editor | |
| Publisher | Elsevier |
| Date | October 2013 |
| Place | |
| ISSN number | 1047-3203 |
| ISBN number | |
| Key words | Automated textile inspection, Fabric defect detection, Gabor filters, Principal Component Analysis, TILDA, Manual defect annotation, Detection rate, False alarm rate |
| Abstract | This paper describes an algorithm for texture defect detection in uniform and structured fabrics, which has been tested on the TILDA image database. The proposed approach is structured in a feature extraction phase, which relies on a complex symmetric Gabor filter bank and Principal Component Analysis (PCA), and on a defect identification phase, which is based on the Euclidean norm of features and on the comparison with fabric type specific parameters. Our analysis is performed on a patch basis, instead of considering single pixels. The performance has been evaluated with uniformly textured fabrics and fabrics with visible texture and grid-like structures, using as reference defect locations identified by human observers. The results show that our algorithm outperforms previous approaches in most cases, achieving a detection rate of 98.8% and a false alarm rate as low as 0.20–0.37%, whereas for heavily structured yarns misdetection rate can be as low as 5%. |
| URL | http://www.sciencedirect.com/science/article/pii/S1047320313001119 |
| DOI | http://dx.doi.org/10.1016/j.jvcir.2013.05.011 |
| Other information | |
| Paper |  (portable document format, 1840541 Bytes) |