Entropy-Based Approach to Analyze and Classify Mineral Aggregates
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2011
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Resumo |
This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates. CNPq, Brazil[301303/06-1] FAPESP, Brazil[2007/01128-0] Fundacao Araucaria, Brazil |
Identificador |
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.25, n.1, p.75-84, 2011 0887-3801 http://producao.usp.br/handle/BDPI/29005 10.1061/(ASCE)CP.1943-5487.0000071 |
Idioma(s) |
eng |
Publicador |
ASCE-AMER SOC CIVIL ENGINEERS |
Relação |
Journal of Computing in Civil Engineering |
Direitos |
restrictedAccess Copyright ASCE-AMER SOC CIVIL ENGINEERS |
Palavras-Chave | #Image processing #Entropy #Classification #Adaptive resonance theory (ART) #Self-organizing novelty detection (SONDE) #Mineral aggregate #WEIGHTED MOVING AVERAGES #NEURAL-NETWORK #MACHINE VISION #CLASSIFICATION #RECOGNITION #ART #Computer Science, Interdisciplinary Applications #Engineering, Civil |
Tipo |
article original article publishedVersion |