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Reseach Article

Color Content based Image and Video Retrieval

Published on February 2015 by S. M. Chavan, A. N. Ghule, C. M. Gaikwad
International Conference on Advances in Science and Technology
Foundation of Computer Science USA
ICAST2014 - Number 2
February 2015
Authors: S. M. Chavan, A. N. Ghule, C. M. Gaikwad
35a572ec-e424-4a44-98cd-634fd1db8b46

S. M. Chavan, A. N. Ghule, C. M. Gaikwad . Color Content based Image and Video Retrieval. International Conference on Advances in Science and Technology. ICAST2014, 2 (February 2015), 23-26.

@article{
author = { S. M. Chavan, A. N. Ghule, C. M. Gaikwad },
title = { Color Content based Image and Video Retrieval },
journal = { International Conference on Advances in Science and Technology },
issue_date = { February 2015 },
volume = { ICAST2014 },
number = { 2 },
month = { February },
year = { 2015 },
issn = 0975-8887,
pages = { 23-26 },
numpages = 4,
url = { /proceedings/icast2014/number2/19479-5025/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Science and Technology
%A S. M. Chavan
%A A. N. Ghule
%A C. M. Gaikwad
%T Color Content based Image and Video Retrieval
%J International Conference on Advances in Science and Technology
%@ 0975-8887
%V ICAST2014
%N 2
%P 23-26
%D 2015
%I International Journal of Computer Applications
Abstract

At the present time content-based image and video retrieval is a rising technology. There are considerable challenges involved in the adaptation of image database and video database for the effective retrieval procedure. We can suggest a techniques using video and image retrieval that can be useful in the real world. Retrieval of information according to the user's requirement is the need today. Content based video retrieval system, works as user to retrieve a video within a potentially large created database of images and videos. Content-based video retrieval systems are less common than image retrieval systems and also an upcoming research area. Features like texture, color and shape are considered for retrieval. The main advantage of the system is it compares image database to retrieve the required video, each feature of the video, and the performance is analyzed. Content based video retrieval has applications in different areas such as news, advertizing, video archive, education system and medical sciences etc.

References
  1. Dr. Sudeep D. Thepade, Ajay A. Narvekar ,Ameya V. Nawale , May 2013, Color Content Based Video Retrieval Using Discrete Cosine Transform Applied On Rows and Columns of Video Frames with RGB Color Space.
  2. Smita Chavan and Shubhangi Sapkal, December 2013 Color Content based Video Retrieval.
  3. Smita Chavan, May - August 2014 Color Based Video Retrieval Using Block and Global Methods
  4. R. Venkata Ramana Chary, Dr. D. Rajya Lakshmi and Dr. K. V. N Sunitha, March 2012 ,Feature Extraction Methods for Color Image Similarity Advanced computing.
  5. B. V Patel and B B Meshram, April 2012,Content Based Video Retrieval Systems.
  6. Y. Alp Aslandogan and Clement T. Yu , January/February 1999. Techniques and Systems for Image and Video Retrieval.
  7. Jun Yue, Zhenbo Li , Lu Liu , Zetian Fu ,2011 ,Content-based image retrieval using color and texture fused features.
  8. Ch. Kavitha Dr. B. Prabhakara Rao Dr. A. Govardhan February 2011,Image Retrieval Based on Color and Texture Features of the Image Sub-blocks.
  9. Bouke Huurnink, Cees G. M. Snoek, Maarten de Rijke, and Arnold W. M. Smeulders, AUGUST 2012,Content-BasedAnalysis Improves Audiovisual Archive Retrieval IEEE Transactions on Multimedia.
  10. N. Kumaran, Dr. R. Bhavani and E. Elamathi, International conference on Communication and Signal Processing, April 3-5, 2013, India, MRI Image Retrieval based on Texture Spectrum and Edge Histogram Features.
  11. P. Muneesawang, L. Guan, IEEE Transactions on Multimedia 6 (2004) 703–716. An interactive Approach for CBIR using a network of radial basis Functions.
  12. J. R. Bach, C. Fuller, A. Gupta, et al. , SPIE 2670, 23, San Jose, CA, 1996, pp. 76–87, Virage image search engine: an open framework for image management.
Index Terms

Computer Science
Information Sciences

Keywords

Color Features Euclidean Distance Feature Extraction Retrieval Techniques.