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

Abstract

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.

Authors and Affiliations

Ranya Al Darwich, Laurent Babout, Krzysztof Strzecha

Keywords

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  • EP ID EP226997
  • DOI 10.5604/01.3001.0010.5213
  • Views 121
  • Downloads 0

How To Cite

Ranya Al Darwich, Laurent Babout, Krzysztof Strzecha (2017). K-MEANS CLUSTERING IN TEXTURED IMAGE: EXAMPLE OF LAMELLAR MICROSTRUCTURE IN TITANIUM ALLOYS. Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska, 7(3), 43-46. https://www.europub.co.uk/articles/-A-226997