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(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 recognition based on diffusion in networks

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Author(s):
Goncalves, Wesley Nunes [1, 2] ; da Silva, Nubia Rosa [3] ; Costa, Luciano da Fontoura [1] ; Bruno, Odemir Martinez [1, 3]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Inst Phys, POB 369, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Fed Mato Grosso do Sul, CPPP, BR-79907414 Ponta Pora, MS - Brazil
[3] Univ Sao Paulo, Inst Math & Comp Sci, Ave Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: INFORMATION SCIENCES; v. 364, p. 51-71, OCT 10 2016.
Web of Science Citations: 4
Abstract

Much work has been done in the field of texture analysis and classification. While promising classification methods have been proposed, most of them rely on classical image analysis approaches. This paper presents a texture classification method based on diffusion in directed networks. First, an image is modeled as a directed network by mapping each pixel as a node and connecting two nodes up to a maximum distance r. To reveal texture properties, links between two nodes are removed based on the pixel intensity difference. Once such a network is obtained, the activity of each node is estimated by random walks and combined into a histogram to describe the image. The main contribution of this paper is the use of directed networks, which tends to provide better performance than in undirected cases. Also, we have shown that the activity induced on these networks can be effectively used as texture descriptor. Experimental results show that the proposed method is favorably compared to traditional texture methods on widely used texture datasets. The proposed method is also found to be promising for plant species classification using samples of leaf texture. (C) 2016 Published by Elsevier. Inc. (AU)

FAPESP's process: 11/01523-1 - Computer vision methods applied to the identification and analysis of plants
Grantee:Odemir Martinez Bruno
Support type: Regular Research Grants
FAPESP's process: 11/21467-9 - Heterogeneous pattern recognition ánd its applications ín biology ánd nanotechnology
Grantee:Núbia Rosa da Silva
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 10/08614-0 - Static ánd dynamic texture analysis ánd their applications ín biology ánd nanotechnology
Grantee:Wesley Nunes Gonçalves
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants
FAPESP's process: 99/12765-2 - Development and assessment of novel and accurate methods in shape analysis and computer vision
Grantee:Luciano da Fontoura Costa
Support type: Research Projects - Thematic Grants