K-MEANS CLUSTERING IN TEXTURED IMAGE: EXAMPLE OF LAMELLAR MICROSTRUCTURE IN TITANIUM ALLOYS

This paper presents an implementation of the k-means clustering method, to segment cross sections of X-ray micro tomographic images of lamellar Titanium alloys. It proposes an approach for estimating the optimal number of clusters by analyzing the histogram of the local orientation map of the image...

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Bibliographic Details
Main Authors: Ranya Al Darwich, Laurent Babout, Krzysztof Strzecha
Format: Article
Language:English
Published: Lublin University of Technology 2019-09-01
Series:Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
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Online Access:https://ph.pollub.pl/index.php/iapgos/article/view/1365
Description
Summary:This paper presents an implementation of the k-means clustering method, to segment cross sections of X-ray micro tomographic images of lamellar Titanium alloys. It proposes an approach for estimating the optimal number of clusters by analyzing the histogram of the local orientation map of the image and the choice of the cluster centroids used to initialize k-means. This is compared with the classical method considering random coordinates of the clusters.
ISSN:2083-0157
2391-6761