Name
Title | ||
|---|---|---|
Supervised texture classification by integration of multiple texture methods and evaluation windows |
Abstract | ||
|---|---|---|
Pixel-based texture classifiers and segmenters typically combine texture feature extraction methods belonging to a same family. Each method is evaluated over square windows of the same size, which is chosen experimentally. This paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods from different families, with each method being evaluated over multiple windows of different size. Experimental results show that this integration scheme leads to significantly better results than well-known supervised and unsupervised texture classifiers based on specific families of texture methods. A practical application to fabric defect detection is also presented. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.imavis.2006.05.023 | Image Vision Comput. |
Keywords | Field | DocType |
multiple texture feature extraction,texture method,evaluation windows,unsupervised texture,multiple texture method,edge flow,kullback j -divergence,different size,fabric defect detection,multiple evaluation windows,different family,square windows,better result,multiple windows,pixel-based texture classifier,lbp,jseg,multiple texture methods,texture feature extraction method,meastex,supervised texture classification | Computer vision,Texture compression,Pattern recognition,Image texture,Feature extraction,Artificial intelligence,Pixel,Classifier (linguistics),Texture filtering,Mathematics | Journal |
Volume | Issue | ISSN |
25 | 7 | Image and Vision Computing |
Citations | PageRank | References |
16 | 0.75 | 25 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Ángel Garcia | 1 | 220 | 24.41 |
| Domènec Puig | 2 | 84 | 7.98 |