Defect detection in textured materials using Gabor filters
This paper investigates various approaches for automated inspection of textured materials using Gabor wavelet features. A new supervised defect detection approach to detect a class of defects in textile webs is proposed. Unsupervised web inspection using a multichannel filtering scheme is investigat...
Saved in:
Published in | IEEE transactions on industry applications Vol. 38; no. 2; pp. 425 - 440 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.03.2002
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | This paper investigates various approaches for automated inspection of textured materials using Gabor wavelet features. A new supervised defect detection approach to detect a class of defects in textile webs is proposed. Unsupervised web inspection using a multichannel filtering scheme is investigated. A new data fusion scheme to multiplex the information from the different channels is proposed. Various factors interacting the tradeoff for performance and computational load are discussed. This scheme establishes high computational savings over the previously proposed approaches and results in high quality of defect detection. Final acceptance of visual inspection systems depends on economical aspects as well. Therefore, a new low-cost solution for fast web inspection is also included in this paper. The experimental results conducted on real fabric defects for various approaches proposed in this paper confirm their usefulness. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0093-9994 1939-9367 |
DOI: | 10.1109/28.993164 |