Name
Title | ||
|---|---|---|
Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets. |
Abstract | ||
|---|---|---|
Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterise different textures. In this study, the authors assess the influence of the chosen wavelet and propose to use the recently introduced empirical wavelets. We show that the adaptability of the empirical wavelet permits to reach better results than classic wavelets. To focus... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-ipr.2017.1005 | IET Image Processing |
Keywords | Field | DocType |
image segmentation,image texture,wavelet transforms | Adaptability,Computer vision,Pattern recognition,Segmentation,Artificial intelligence,Mathematics,Wavelet | Journal |
Volume | Issue | ISSN |
12 | 9 | 1751-9659 |
Citations | PageRank | References |
3 | 0.40 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Huang | 1 | 12 | 7.67 |
| Valentin De Bortoli | 2 | 3 | 0.40 |
| Fugen Zhou | 3 | 9 | 1.67 |
| Jérôme Gilles | 4 | 6 | 2.13 |