Varma, M. ; Garg, R. (2007) Locally Invariant Fractal Features for Statistical Texture Classification In: Proceedings of the IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil.
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Abstract
We address the problem of developing discriminative, yet invariant, features for texture classification. Texture variations due to changes in scale are amongst the hardest to handle. One of the most successful methods of dealing with such variations is based on choosing interest points and selecting their characteristic scales [Lazebnik et al. PAMI 2005]. However, selecting a characteristic scale can be unstable for many textures. Furthermore, the reliance on an interest point detector and the inability to evaluate features densely can be serious limitations.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to IEEE International Conference on Computer Vision. |
| ID Code: | 119704 |
| Deposited On: | 16 Jun 2021 09:55 |
| Last Modified: | 16 Jun 2021 09:55 |
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