K-MEANS CLUSTERING IN TEXTURED IMAGE: EXAMPLE OF LAMELLAR MICROSTRUCTURE IN TITANIUM ALLOYS
Ranya Al Darwich
raldarwich@kis.p.lodz.plLodz University of Technology, Institute of Applied Computer Science (Poland)
Laurent Babout
Lodz University of Technology, Institute of Applied Computer Science (Poland)
Krzysztof Strzecha
Lodz University of Technology, Institute of Applied Computer Science (Poland)
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.
Keywords:
k-means clustering, oriented textured, number of clusters, X-ray tomographyReferences
Al Darwich R., Babout L.: Optimization of 3D Local Orientation Map Calculation in the Matlab Framework. IAPGOŚ 2/2015, 22–24.
Google Scholar
Babout L., Jopek Ł., Janaszewski M.: A New Directional Filter Bank for 3D Texture Segmentation: Application to Lamellar Microstructure in Titanium Alloys. MVA 2013, 419–422.
Google Scholar
Babout L., Jopek L., Preuss M.: 3D characterization of trans- and inter-lamellar fatigue crack in (α+β) Ti alloy. Materials Characterization, 98/2014, 130–139.
Google Scholar
Bijnen E.J.: Cluster analysis. Tilburg University Press, Netherlands, 1973.
Google Scholar
Calinski T., Harabasz J.: A dendrite method for cluster analysis. Communications in Statistics, 3/1974, 1–27.
Google Scholar
Comaniciu D., Meer P.: Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24/2002, 603–619.
Google Scholar
Chandler D.: The norm of the Schur product operation. Numerische Mathematik 4.1, 1962, 343–344.
Google Scholar
Duda R.O., Hart P.E.: Pattern Classification and Scene Analysis. Wiley, New York, 1973.
Google Scholar
Jeulin D., Moreaud M.: Segmentation of 2D and 3D textures from estimates of the local orientation. Image Anal Stereo, 27/2008, 183–192.
Google Scholar
Milligan G.W., Cooper M.C.: An examination of procedures for determining the number of clusters in a data set. 1985, 159–179.
Google Scholar
Yan M.: Methods of Determining the Number of Clusters in a Data Set and a New Clustering Criterion. Blacksburg, Virginia 2005.
Google Scholar
Authors
Ranya Al Darwichraldarwich@kis.p.lodz.pl
Lodz University of Technology, Institute of Applied Computer Science Poland
Authors
Laurent BaboutLodz University of Technology, Institute of Applied Computer Science Poland
Authors
Krzysztof StrzechaLodz University of Technology, Institute of Applied Computer Science Poland
Statistics
Abstract views: 212PDF downloads: 70
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Most read articles by the same author(s)
- Laurent Babout , Krzysztof Grudzień, Marcin Janaszewski, Łukasz Jopek, STUDY OF DEGRADATION AND GRANULAR FLOW PROCESSES USING X-RAY IMAGING , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 7 No. 1 (2017)
- Ranya Al Darwich, Laurent Babout, OPTIMIZATION OF 3D LOCAL ORIENTATION MAP CALCULATION IN THE MATLAB FRAMEWORK , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 5 No. 2 (2015)
