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Reseach Article

A Study on Image Retrieval by Low Level Features

by Nareshkumar .s, Vijayarajan .v
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 18
Year of Publication: 2012
Authors: Nareshkumar .s, Vijayarajan .v
10.5120/6203-8747

Nareshkumar .s, Vijayarajan .v . A Study on Image Retrieval by Low Level Features. International Journal of Computer Applications. 43, 18 ( April 2012), 18-21. DOI=10.5120/6203-8747

@article{ 10.5120/6203-8747,
author = { Nareshkumar .s, Vijayarajan .v },
title = { A Study on Image Retrieval by Low Level Features },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 18 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 18-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number18/6203-8747/ },
doi = { 10.5120/6203-8747 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:44.375318+05:30
%A Nareshkumar .s
%A Vijayarajan .v
%T A Study on Image Retrieval by Low Level Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 18
%P 18-21
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In Today's digital world vast amount of digital images are shared in online. When the number of images increased day by day the image retrieval based upon user perception is decreasing. In order to retrieve the relevant image we should need high efficient algorithms as well as retrieval methods. Image indexing plays an important role in image retrieval. Because by means of indexing only we can correlate the images and based on that only we can retrieve relevant images. But indexing also having problem when we had a very huge image database. Usually we are having two kinds of image retrieving methods Text Based IR and Content Based IR. In this paper we are going to see in detail about the methods as well as efficient algorithms for retrieving relevant image.

References
  1. The SMART Retrieval System: Experiments in Automatic Document Processing. Prentice-Hall, 1971.
  2. Gerard Salton and Christopher Buckley. Term-weighting approaches in automatic text retrieval, Information Processing and Management, 1998.
  3. C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Petkovic, and R. Barber. Journal of Intelligent Information Systems, 3(3/4):231–262, July 1994.
  4. Michael J. Swain and Dana H. ballard. Indexing via Color Histograms, University of Rochester, NY 14627, USA.
  5. www. wikipedia. com/precision and recall
  6. C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Petkovic, and R. Barber. Efficient and effective querying by image content. Journal of Intelligent Information Systems, 3(3/4):231–262, July 1994.
  7. M. Stricker and M. Orengo. Similarity of color images. In Storage and Retrieval for Image and Video Databases SPIE, volume 2420, pages 381–392, San Jose, CA, Feb. 1995.
  8. A. Pentland, R. W. Picard, and S. Sclaroff. Photobook: Content-based manipulation of image databases. In B. Furht, editor, Multimedia Tools and Applications, chapter 2, pages 43–80. Kluwer Academic Publishers, 1996.
  9. J. R. Smith. Integrated Spatial and Feature Image Systems: Retrieval, Analysis and Compression. PhD thesis, Columbia University, 1997.
  10. A. Pentland, R. W. Piwd, and S. Sclaroff. Photobook Tools for content-based manipulation of image databases. In Srorage and Retrieval for Image and V i 0 Databases II, volume 2185 of SPIE Proceedingsseries, San Jose, CA, USA, 1994.
  11. W. Y. Ma and B. S. Manjunath. A toolbox for navigating large image databases. In IEEE Internatianal Conference on Image Processing (KIP), Santa Barbara, California, October 1997.
  12. J. R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R Jab. and C. -F. Shu. The Wage image search engine: An open framework for image management. In I. IC. Sethi and R. J. Jain, editors, Storage and Retrieval for Image and V i 0 Databases N, volume 2670 of Proceedings of SPIE, pages 76-87,1996.
Index Terms

Computer Science
Information Sciences

Keywords

Image Retrieval Low Level Features Cbir