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.
|Number of pages||3|
|Journal||Proceedings - International Conference on Pattern Recognition|
|Publication status||Published - Dec 1 2000|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition