Name
Abstract | ||
|---|---|---|
This paper addresses detection of imperfections in repetitive regular structures (textures). Humans can easily find such defects without prior knowledge of the `good' pattern. In this study, it is assumed that structural defects are detected as irregularities, that is, locations of lower regularity. We define pattern regularity features and find defects by robust detection of outliers in the feature space. Two tests are presented to assess the approach. In the first test, diverse texture patterns are processed individually and outliers are searched in each pattern. In the second test, classified defects in a group of textiles are considered. Defect-free patterns are used to learn distance thresholds that separate defects |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ICPR.2000.905390 | ICPR |
Keywords | Field | DocType |
diverse texture pattern,defect detection,repetitive regular structures,lower regularity,pattern regularity feature,pattern classification,pattern regularity,prior knowledge,outliers,automatic optical inspection,feature extraction,defect-free pattern,distance threshold,robust detection,general approach,textile inspection,structural defects,feature space,image texture,paper addresses detection,textile industry,classified defect,design methodology,inspection,textiles,testing,automation,computer vision,robustness,application software | Computer vision,Feature vector,Pattern recognition,Computer science,Image texture,Outlier,Automation,Feature extraction,Robustness (computer science),Design methods,Artificial intelligence,Application software | Conference |
Volume | ISSN | ISBN |
1 | 1051-4651 | 0-7695-0750-6 |
Citations | PageRank | References |
4 | 0.41 | 8 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chetverikov, D. | 1 | 956 | 99.89 |