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Image Segmentation for Nature Images using K-Mean and Fuzzy C-Mean

Published on March 2012 by Anita V. Gawand, Prashant Lokhande, Sulekha daware, Umesh Kulkarni
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International Conference on Recent Trends in Information Technology and Computer Science
Foundation of Computer Science USA
ICRTITCS - Number 2
March 2012
Authors: Anita V. Gawand, Prashant Lokhande, Sulekha daware, Umesh Kulkarni
99d6be01-7503-4a6e-8448-12be6147244a

Anita V. Gawand, Prashant Lokhande, Sulekha daware, Umesh Kulkarni . Image Segmentation for Nature Images using K-Mean and Fuzzy C-Mean. International Conference on Recent Trends in Information Technology and Computer Science. ICRTITCS, 2 (March 2012), 37-40.

@article{
author = { Anita V. Gawand, Prashant Lokhande, Sulekha daware, Umesh Kulkarni },
title = { Image Segmentation for Nature Images using K-Mean and Fuzzy C-Mean },
journal = { International Conference on Recent Trends in Information Technology and Computer Science },
issue_date = { March 2012 },
volume = { ICRTITCS },
number = { 2 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 37-40 },
numpages = 4,
url = { /proceedings/icrtitcs/number2/5184-1016/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Information Technology and Computer Science
%A Anita V. Gawand
%A Prashant Lokhande
%A Sulekha daware
%A Umesh Kulkarni
%T Image Segmentation for Nature Images using K-Mean and Fuzzy C-Mean
%J International Conference on Recent Trends in Information Technology and Computer Science
%@ 0975-8887
%V ICRTITCS
%N 2
%P 37-40
%D 2012
%I International Journal of Computer Applications
Abstract

Clustering can be considered the most important unsupervised learning problem. It deals with finding a structure in a collection of unlabeled data. We defined cluster is process of organizing objects into group whose member are similar in some way. In my paper we taken natural image and we apply unsupervised learning algorithm k-mean and Fuzzy c-mean that solve the well known clustering problem.

References
  1. J. Shi, J. Malik, Normalized cuts and image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 22 (8) (2000) 888–905.
  2. S.C. Zhu, A. Yuille, Region competition: unifying snakes, region growing, and byes/mdl for multi-band image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 18 (9) (1996) 884–900.
  3. D. Comaniciu, P. Meer, Mean shift: a robust approach toward feature space analysis, IEEE Trans. Pattern Anal. Mach. Intell. 24 (5) (2002) 1–18.
  4. T.N. Pappas, An adaptive clustering algorithm for image segmentation, IEEE Trans. Signal Process. 10 (1) (1992) 901–914.
  5. J. Canny, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8 (6) (1986) 679–698.
  6. An Efficient k-means Clustering Algorithm: Analysis and Implementation by Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth. Silverman Angela Y. Wu.
  7. Research issues on K-means Algorithm: An Experimental Trial Using Matlab by Joaquin Perez Ortega, Ma. Del Rocio Boone Rojas and Maria J. Somodevil Garcia.
  8. The k-means algorithm - Notes by Tan, Steinbach, Kumar Ghosh.
  9. http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/kmeans.html/cmean.html
  10. k-means clustering by ke chen.
  11. Fuzzy c-means by Balaji K and Juby N Zacharias.
  12. Fast and Robust Fuzzy C-Means Clustering Algorithms Incorporating Local Information for Image Segmentation by Weiling Cai, Songcan Chen and DaoqiangZhang.
  13. Wikipedia: www.wikipedia,org/segmentation
  14. Google:http://sites.google.com/site/dataclusteringalgorithms/k-mean-clustering-algorithm
  15. Google:http://sites.google.com/site/dataclusteringalgorithms/fuzzy-c-mean-clustering-algorithm
  16. We for animals: Awww.weforanimals.com/free-pictures/nature
Index Terms

Computer Science
Information Sciences

Keywords

segmentation k-mean fuzzy c-mean