CFP last date
20 January 2025
Reseach Article

Clustering for Content based Image Retrieval-A Survey

Published on December 2014 by Vijay S Patil, P. J. Deore
National Conference on Advances in Communication and Computing
Foundation of Computer Science USA
NCACC2014 - Number 2
December 2014
Authors: Vijay S Patil, P. J. Deore
dfe244d1-e487-4aaa-a8fc-6a04ea16ea2f

Vijay S Patil, P. J. Deore . Clustering for Content based Image Retrieval-A Survey. National Conference on Advances in Communication and Computing. NCACC2014, 2 (December 2014), 12-14.

@article{
author = { Vijay S Patil, P. J. Deore },
title = { Clustering for Content based Image Retrieval-A Survey },
journal = { National Conference on Advances in Communication and Computing },
issue_date = { December 2014 },
volume = { NCACC2014 },
number = { 2 },
month = { December },
year = { 2014 },
issn = 0975-8887,
pages = { 12-14 },
numpages = 3,
url = { /proceedings/ncacc2014/number2/19127-2014/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Communication and Computing
%A Vijay S Patil
%A P. J. Deore
%T Clustering for Content based Image Retrieval-A Survey
%J National Conference on Advances in Communication and Computing
%@ 0975-8887
%V NCACC2014
%N 2
%P 12-14
%D 2014
%I International Journal of Computer Applications
Abstract

Clustering is the technique of classifying substance into sets of related or unrelated group of objects, basically Clustering is data analysis method for pattern recognition, feature extraction. Clustering perform very important task in CBIR to improve the accuracy in an image retrieval process.

References
  1. A. K. Jain, M. N. Murtyin, P. J. Flynn, "Data Clustering: A Review", ACM Computing Surveys, Vol. 31, No. 3, 1999.
  2. Kanungo Tapas, Mount D. M. , Netanyahu N. S. , Piatko C. D. , Silverman R. , Wu A. Y. , "An efficient k-means clustering algorithm: analysis and implementation", Pattern Analysis and Machine Intelligence, IEEE Transactions , vol. 24, no. 7, pp. 881,892, 2002.
  3. Yuchai Wan, Xiabi Liu, Jie Bing and Yunpeng Chen, "Online image classifier learning for Google image search improvement", IEEE International Conference on Information and Automation (ICIA), pp. 103 – 110, 2011.
  4. Sabzi A, Farjami Y. , ZiHayat M. , "An improved fuzzy k-medoids clustering algorithm with optimized number of clusters", Hybrid Intelligent Systems (HIS), 11th International Conference, pp. 206 – 210, 2011.
  5. Hongli Xu, De Xu, Enai Lin, "An applicable hierarchical clustering algorithm for content-based image retrieval", Computer vision/computer graphics collaboration techniques, 3rd international conference, pp. 82-92 Springer-Verlag Berlin, Heidelberg, 2007.
  6. Jiawei Han. 2006, "Data Mining: Concepts and Techniques" Elsevier Inc.
  7. Shih-Sian Cheng, Hsin-Chia Fu, Hsin-Min Wang, "Model-Based Clustering by Probabilistic Self Organizing Maps", IEEE transactions on neural networks, Vol. 20, No. 5, 2009.
  8. Khaled Alsabti, Sanjay Ranka, Vineet Singh, "An Efficient K-Means Clustering Algorithm", Information Technology Lab (ITL) of Hitachi America, Ltd.
  9. Mingyan Yu , Haiyuan Liu, Yanhang Qiu, Ying Yan, "An improved EM algorithm for content based image retrieval", Computer Science and Service System (CSSS), International Conference, pp 2047 – 2050, 2011.
  10. Guannan Zhao, Shijian Luo , Ji He, Ying Yan, "Style matching model-based recommend system for online shopping", Computer-Aided Industrial Design & Conceptual Design, IEEE 10th International Conference ,pp. 1995 – 1999, 2009.
  11. K L Du, "Clustering: A Neural Network approach", 2009 Elsevier, Neural Networks Vol. 23, No. 1, pp. 89-107, 2010.
  12. Krakovsky, R. , Forgac, R. , "Neural network approach to multidimensional data classification via clustering", IEEE 9th International Symposium on Intelligent Systems and Informatics, pp 169 - 174, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Cbir Partitioning Hierarchical Algorithms Model Based.