Abstract
The wavelet transform (WT) has been developed over 20 years and successfully applied in defect detection on plain (unpatterned) fabric. This paper is on the use of the wavelet transform to develop an automated visual inspection method for defect detection on patterned fabric. A method called direct thresholding (DT) based on WT detailed subimages has been developed. The golden image subtraction method (GIS) is also introduced. GIS is an efficient and fast method, which can segment out the defective regions on patterned fabric effectively. In this paper, the method of wavelet preprocessed golden image subtraction (WGIS) has been developed for defect detection on patterned fabric or repetitive patterned texture. This paper also presents a comparison of the three methods. It can be concluded that the WGIS method provides the best detection result. The overall detection success rate is 96.7% with 30 defect-free images and 30 defective patterned images for one common kind of patterned Jacquard fabric.
| Original language | English |
|---|---|
| Pages (from-to) | 559-576 |
| Number of pages | 18 |
| Journal | Pattern Recognition |
| Volume | 38 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Apr 2005 |
Scopus Subject Areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
User-Defined Keywords
- Defect detection
- Patterned fabric inspection
- Patterned texture
- Texture analysis
- Wavelet transform