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Analysis of Spatial Features in CBIR System

by Minakshi Kaushik, Rahul Sharma, Ankit Vidhyarthi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 17
Year of Publication: 2012
Authors: Minakshi Kaushik, Rahul Sharma, Ankit Vidhyarthi
10.5120/8657-2477

Minakshi Kaushik, Rahul Sharma, Ankit Vidhyarthi . Analysis of Spatial Features in CBIR System. International Journal of Computer Applications. 54, 17 ( September 2012), 11-15. DOI=10.5120/8657-2477

@article{ 10.5120/8657-2477,
author = { Minakshi Kaushik, Rahul Sharma, Ankit Vidhyarthi },
title = { Analysis of Spatial Features in CBIR System },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 17 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number17/8657-2477/ },
doi = { 10.5120/8657-2477 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:55.804642+05:30
%A Minakshi Kaushik
%A Rahul Sharma
%A Ankit Vidhyarthi
%T Analysis of Spatial Features in CBIR System
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 17
%P 11-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content based image retrieval from large database has become an area of wide interest nowadays in many applications. Content-based image retrieval (CBIR) technique use image content to search and retrieve digital images. Content-based image retrieval (CBIR) is an important research area for manipulating large amount of image databases. In this paper the analysis work is done for finding the spatial features and collects them into a frame to view all the spatial features and the scope of implementing these features into the image retrieval. The commercial image search engines available as on date are: QBIC, VisualSeek, Virage, Netra, PicSOM, FIRE, AltaVista, etc. Region-Based Image Retrieval (RBIR) is a promising extension of CBIR. The shape and spatial features are quite simple to derive and effective, and can be extracted in real time. Our analysis is able to propose a system that has the advantage of increasing the retrieval accuracy and decreasing the retrieval time.

References
  1. S. R. Kodituwakku "Comparison of Color Features for Image Retrieval", et al. / Indian Journal of Computer Science and Engineering Vol. 1 No. 3 207-211S. R
  2. Shriram K V, P. L. K. Priyadarsini, "CBIR – An analysis and suggestions for improvement", International Journal of Computer Applications (0975 – 8887) Volume 42– No. 14, March 2012
  3. Selvarajah and S. R. Kodituwakku (2011), "Analysis and Comparison of Texture Features for Content Based Image Retrieval. " International Journal of Latest Trends in Computing (E-ISSN: 2045-5364) 108 Volume 2, Issue 1, March 2011
  4. P. B. Thawari & N. J. Janwe (2011), "CBIR Based on color and texture", International Journal of Information Technology and Knowledge Management January-June 2011, Volume 4, No. 1, pp. 129-132
  5. Arnold W. M. Smeulders, Senior Member, IEEE, Marcel Worring, Simone Santini, Member, IEEE, Amarnath Gupta, Member, IEEE, and Ramesh Jain, Fellow, IEEE(2000), "Content-Based Image Retrieval at the End of the Early Years", IEEE Transactions on pattern analysis and machine intelligence, VOL. 22, NO. 12, December 2000
  6. Hiremath P. S, Jagadeesh Pujari, "Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image. "
  7. Shriram K V and P. L. K. Priyadarsini (2012), "CBIR – An analysis and suggestions for improvement", International Journal of Computer Applications (0975 – 8887) Volume 42– No. 14, March 2012
  8. B. V. Ramana Reddy, A. Suresh, M. Radhika Mani3, and V. Vijaya Kumar(2009), "Classification of Textures Based on Features Extracted from Preprocessing Images on Random Windows", International Journal of Advanced Science and Technology Volume 9, August, 2009
  9. Noah Keen ,"Color Moments" February 10, 2005
  10. Greg Pass Ramin Zabih_ Justin Miller, "Comparing Images Using Color Coherence Vectors" Cornell University Ithaca, NY 14853
  11. P. S. Hiremath and Jagadeesh Pujari , " Content Based Image Retrieval based on Color, Texture and Shape features using Image and its complement"
  12. Vaibhav Gupta ,(2012), "Evolution of CBIR approaches for differently sized images" International Journal on Computer Science and Engineering (IJCSE), Vol. 4 No. 01 January 2012
  13. Pradnya Rane ,Pallavi Kulkarni, Suchita Patil and B. B. Meshram, "Feature based image retrieval of images for CBIR", IJCEM International Journal of Computational Engineering & Management, Vol. 14, October 2011
  14. Swati V. Sakhare & Vrushali G. Nasre, "Design of Feature Extraction in Content Based Image Retrieval (CBIR) using Color and Texture", International Journal of Computer Science & Informatics, Volume-I, Issue-II, 2011
  15. Alaa Al-Hamami and Hisham Al-Rashdan(2010), "Improving the Effectiveness of the color coherence vector",The International Arab Journal of Information Technology, Vol. 7, No. 3, July 2010
Index Terms

Computer Science
Information Sciences

Keywords

Feature Vector CBIR Edge Histogram Color Texture

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