| Full text | |
| Author(s): |
Total Authors: 2
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| Affiliation: | [1] Univ Fed Sao Carlos, Sao Carlos Inst Phys IFSC, Sci Comp Grp, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 1
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| Document type: | Journal article |
| Source: | PATTERN RECOGNITION; v. 46, n. 11, p. 2953-2968, NOV 2013. |
| Web of Science Citations: | 14 |
| Abstract | |
In this paper, we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets. (C) 2013 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 11/01523-1 - Computer vision methods applied to the identification and analysis of plants |
| Grantee: | Odemir Martinez Bruno |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 10/08614-0 - Static and Dynamic Texture Analysis and their Applications in Biology and Nanotechnology |
| Grantee: | Wesley Nunes Gonçalves |
| Support Opportunities: | Scholarships in Brazil - Doctorate |