Name
Abstract | ||
|---|---|---|
The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-69812-8_68 | ICIAR |
Keywords | Field | DocType |
discriminative power,image orientation,texture descriptors,analysed texture descriptors,multi-resolution texture classification,texture classification scheme,standard texture databases,local image,gaussian function,texture classification process,multi-resolution texture analysis scheme,svm,image processing | Computer vision,Texture compression,Pattern recognition,Bidirectional texture function,Image texture,Computer science,Support vector machine,Orientation (computer vision),Artificial intelligence,Discriminative model,Gaussian function,Texture filtering | Conference |
Volume | ISSN | Citations |
5112 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ovidiu Ghita | 1 | 234 | 18.12 |
| Paul F. Whelan | 2 | 561 | 39.95 |
| Dana E. Ilea | 3 | 81 | 3.71 |