Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Full text
Author(s):
Backes, Andre R. [1] ; Martinez, Alexandre S. [2, 3] ; Bruno, Odemir M. [4]
Total Authors: 3
Affiliation:
[1] Univ Fed Uberlandia, Fac Comp, BR-38408100 Uberlandia, MG - Brazil
[2] Univ Sao Paulo, FFCLRP, BR-14040901 Ribeirao Preto, SP - Brazil
[3] Inst Natl Ciencia & Tecnol Sistemas Complexos, BR-14040901 Ribeirao Preto, SP - Brazil
[4] Univ Sao Paulo, IFSC, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: PATTERN RECOGNITION; v. 44, n. 8, p. 1684-1689, AUG 2011.
Web of Science Citations: 19
Abstract

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved. (AU)