Entropy-Based Approach to Analyze and Classify Mineral AggregatesSource: Journal of Computing in Civil Engineering:;2011:;Volume ( 025 ):;issue: 001Author:Lilian Tais de Gouveia
,
Luciano da Fontoura Costa
,
Luciano José Senger
,
Marcelo Keese Albertini
,
Rodrigo Fernandes de Mello
DOI: 10.1061/(ASCE)CP.1943-5487.0000071Publisher: American Society of Civil Engineers
Abstract: 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.
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contributor author | Lilian Tais de Gouveia | |
contributor author | Luciano da Fontoura Costa | |
contributor author | Luciano José Senger | |
contributor author | Marcelo Keese Albertini | |
contributor author | Rodrigo Fernandes de Mello | |
date accessioned | 2017-05-08T21:40:19Z | |
date available | 2017-05-08T21:40:19Z | |
date copyright | January 2011 | |
date issued | 2011 | |
identifier other | %28asce%29cp%2E1943-5487%2E0000078.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/59038 | |
description abstract | 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. | |
publisher | American Society of Civil Engineers | |
title | Entropy-Based Approach to Analyze and Classify Mineral Aggregates | |
type | Journal Paper | |
journal volume | 25 | |
journal issue | 1 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)CP.1943-5487.0000071 | |
tree | Journal of Computing in Civil Engineering:;2011:;Volume ( 025 ):;issue: 001 | |
contenttype | Fulltext |