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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.)

Supervised Classification of Basaltic Aggregate Particles Based on Texture Properties

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de Gouveia, Lilian Tais [1] ; de Arruda, Guilherme Ferraz [2] ; Rodrigues, Francisco Aparecido [2] ; Senger, Luciano Jose [3] ; Costa, Luciano da Fontoura [1]
Total Authors: 5
[1] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13560970 Sao Paulo - Brazil
[2] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat Aplicada & Estat, BR-13560970 Sao Carlos, SP - Brazil
[3] Univ Estadual Ponta Grossa, Dept Informat, BR-84030900 Ponta Grossa, PR - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF COMPUTING IN CIVIL ENGINEERING; v. 27, n. 2, p. 177-182, MAR 2013.
Web of Science Citations: 1

The strength and durability of materials produced from aggregates (e. g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials. DOI: 10.1061/(ASCE)CP.1943-5487.0000212. (C) 2013 American Society of Civil Engineers. (AU)

FAPESP's process: 10/19440-2 - Characterization, analysis, simulation and classification of complex networks
Grantee:Francisco Aparecido Rodrigues
Support type: Regular Research Grants
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