Supervised Classification of Basaltic Aggregate Particles Based on Texture Properties

Autor(es)

de Gouveia, Lilian Tais ^[1] ; de Arruda, Guilherme Ferraz ^[2] ; Rodrigues, Francisco Aparecido ^[2] ; Senger, Luciano Jose ^[3] ; Costa, Luciano da Fontoura ^[1]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF COMPUTING IN CIVIL ENGINEERING; v. 27, n. 2, p. 177-182, MAR 2013.
• Citações Web of Science: 1

Resumo

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)

• Processo FAPESP: 10/19440-2 - Caracterização, análise, simulação e classificação de redes complexas
• Beneficiário: Francisco Aparecido Rodrigues
• Linha de fomento: Auxílio à Pesquisa - Regular
• Processo FAPESP: 07/01128-0 - Predicao do comportamento estrutural e mecanico de misturas de concreto asfaltico utilizando tecnicas de processamento digital de imagens
• Beneficiário: Lilian Tais de Gouveia
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 05/00587-5 - Modelagem por redes (grafos) e técnicas de reconhecimento de padrões: estrutura, dinâmica e aplicações
• Beneficiário: Roberto Marcondes Cesar Junior
• Linha de fomento: Auxílio à Pesquisa - Temático