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Reseach Article

Efficient Image Retrieval using Region based Image Retrieval

Published on June 2013 by Ramesh K Kulkarni, Niket Amoda
International Conference and workshop on Advanced Computing 2013
Foundation of Computer Science USA
ICWAC - Number 2
June 2013
Authors: Ramesh K Kulkarni, Niket Amoda
397ce7e7-9fd0-4211-98a9-91c697e58553

Ramesh K Kulkarni, Niket Amoda . Efficient Image Retrieval using Region based Image Retrieval. International Conference and workshop on Advanced Computing 2013. ICWAC, 2 (June 2013), 0-0.

@article{
author = { Ramesh K Kulkarni, Niket Amoda },
title = { Efficient Image Retrieval using Region based Image Retrieval },
journal = { International Conference and workshop on Advanced Computing 2013 },
issue_date = { June 2013 },
volume = { ICWAC },
number = { 2 },
month = { June },
year = { 2013 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/icwac/number2/483-1317/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and workshop on Advanced Computing 2013
%A Ramesh K Kulkarni
%A Niket Amoda
%T Efficient Image Retrieval using Region based Image Retrieval
%J International Conference and workshop on Advanced Computing 2013
%@ 2249-0868
%V ICWAC
%N 2
%P 0-0
%D 2013
%I International Journal of Applied Information Systems
Abstract

Early image retrieval techniques were based on textual annotation of images. Annotating images manually is a cumbersome and expensive task for large image databases, and is often subjective, context-sensitive and incomplete. Content based image retrieval, uses the visual contents of an image such as color, shape, texture, and spatial layout to represent and index the image. The Region Based Image Retrieval (RBIR) system uses the Discrete Wavelet Transform (DWT) and a k-means clustering algorithm to segment an image into regions. Each region is represented by means of a set of features and the similarity between regions is measured using a specific metric function on such features.

References
  1. D. Lowe, "Object recognition from local scale-invariant features," in ICCV, 1999, pp. 1150–1157.
  2. Y. J. Zhang "A survey on evaluation methods for image segmentation", Pattern Recognition 29 (8) (1996) 1335 - 1340
  3. A. Jain, "Data clustering: 50 years beyond k-means," Pattern Recognition Letters, vol. 31, no. 8, pp. 651 – 666, June 2010.
  4. W. Zhao, H. Ma, Q. He, "Parallel K-Means Clustering Based on MapReduce," in: Cloud Computing, vol. 5931, pp. 674-679, 2009.
  5. W. D. Arthur, S. Vassilvitskii, "K-means++: the Advantages of careful seeding," in Proc. 2007 Symposium on Discrete Algorithms, pp. 1027-1035.
  6. Rafael C. Gonzalez, Richard E. Woods, " Digital Image Processing" , Second Edition, Prentice Hall Upper Saddle River, New Jersey 07458, TA1632. G66 2001, 698-740
  7. Fast Multiresolution Image Querying, International Conference on Computer Graphics and Interactive Techniques, 1995: Charles E. Jacobs, Adam Finkelstein, David H. Salesin
  8. Content-based Image Retrieval, A report to the JISC Technology Applications Programme, 1999: John Eakins, Margaret Graham
  9. Fundamentals of Content-based Image Retrieval, Multimedia Information Retrieval and Management - Technological Fundamentals and Applications, Springer, 2002: Dr. Fuhui Long, Dr. Hongjiang Zhang, Prof. David Dagan Feng
  10. Image Retrieval – Current techniques, Promising directions and Open issues, Journal of Visual Communication and Image Representation, 1999: Yong Rui, Thomas S. Huang, Shih-Fu Chang
  11. Wavelet Based Texture Analysis and Segmentation for Image Retrieval and Fusion, Thesis, University of Bristol, 2002: Paul R. Hill
  12. WINDSURF: A Region Based Image Retrieval System, Proceedings of the 10th International Workshop on Database & Expert Systems Applications, 2000: IlariaBartolini, Paolo Ciaccia, Marco Patella
  13. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan, "Object detection with discriminatively trained part based models," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Content based image retrieval K-Means Algorithm Discrete Wavelet Transform Region Based Image Retrieval