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http://dx.doi.org/10.12989/cac.2014.14.3.315

Automated segmentation of concrete images into microstructures: A comparative study  

Yazdi, Mehran (Department of Electronics and Computer Engineering,Shiraz University)
Sarafrazi, Katayoon (Department of Electronics and Computer Engineering,Shiraz University)
Publication Information
Computers and Concrete / v.14, no.3, 2014 , pp. 315-325 More about this Journal
Abstract
Concrete is an important material in most of civil constructions. Many properties of concrete can be determined through analysis of concrete images. Image segmentation is the first step for the most of these analyses. An automated system for segmentation of concrete images into microstructures using texture analysis is proposed. The performance of five different classifiers has been evaluated and the results show that using an Artificial Neural Network classifier is the best choice for an automatic image segmentation of concrete.
Keywords
microstructural analysis; image segmentation; FLD; KNN; artificial neural networks; SVM; bayesian classification; co-occurrence matrix; texture analysis;
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