CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval

by Sandip S. Patil, Atul V. Dusane
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 17
Year of Publication: 2012
Authors: Sandip S. Patil, Atul V. Dusane
10.5120/8293-1789

Sandip S. Patil, Atul V. Dusane . Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval. International Journal of Computer Applications. 52, 17 ( August 2012), 9-12. DOI=10.5120/8293-1789

@article{ 10.5120/8293-1789,
author = { Sandip S. Patil, Atul V. Dusane },
title = { Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 17 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number17/8293-1789/ },
doi = { 10.5120/8293-1789 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:52:30.984317+05:30
%A Sandip S. Patil
%A Atul V. Dusane
%T Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 17
%P 9-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we use the color feature extraction technique that considers the image color distribution. For the color feature extraction process we use the clustering, where fixed number of clusters and variable number of clusters are formed. The proposed technique preserve the image color distribution and reduces the distortion that occurred during the feature extraction process by using binary quaternion moment preserving (BQMP) technique. With this system we devised efficient relevance feedback to improve the efficiency of the content based image retrieval system. Our Experimental results shows there is an improvement in proposed system over the prior binning technique and ACE.

References
  1. A. Papoulis and S. U. Pillair, Probability, Random Variables, and Stochastic Processes. New York: McGraw-Hill, 2002.
  2. F. Long, H. Zhang, and D. D. Feng, "Fundamentals of content-based image retrieval," in Multimedia Information Retrieval and Management Technological Fundamentals and Applications. New York: Springer-Verlag, 2003.
  3. Mourad Oussalah "Content Based Image Retrieval: Review of State of Art and Future Directions, IEEE Image processing Theory Tools & application 2008.
  4. R. Veltkamp, "Content-based image retrieval system: A survey," University of Utrecht, Tech. Rep. , 2002 vol. 28, no. 9, pp. 23–32, Sep. 1995.
  5. S. Antani, R. Kasturi, and R. Jain, "A survey on the use of pattern recognition methods for abstraction, indexing, and retrieval of images and video," Pattern Recognit. , vol. 35, no. 4, pp. 945–965, 2002.
  6. S. -C. Pei and C. -M. Cheng, "Color image processing by using binary quaternion moment-preserving thresholding technique," IEEE Trans. Image Process. , vol. 8, no. 5, pp. 614–628, May 1999.
  7. W. Chen, W. Liu, M. Chen, "Adaptive Color Feature Extraction Based on Image Color Distributions" IEEE Transaction on image processing, vol 19, No. 8, August 2010.
  8. Y. Rui, T. S. Huang, and S. -F. Chang, "Image retrieval: Current techniques, promising directions, and open issues," J. Vis. Commun. Image Represent. , vol. 10, no. 1, Mar. 1999.
  9. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Contentbased image retrieval at the end of the early years," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 22, no. 12, pp. 1349–1380, Dec. 2000.
Index Terms

Computer Science
Information Sciences

Keywords

content based image retrieval distance measure color histogram color feature extraction relevance feedback similarity measurement

Powered by PhDFocusTM