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Content based Image Retrieval using Color and Texture

by Tasneem Mirza, Rishabh Indoria, Geet Dalwani, Krish Jain
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 141 - Number 7
Year of Publication: 2016
Authors: Tasneem Mirza, Rishabh Indoria, Geet Dalwani, Krish Jain
10.5120/ijca2016909633

Tasneem Mirza, Rishabh Indoria, Geet Dalwani, Krish Jain . Content based Image Retrieval using Color and Texture. International Journal of Computer Applications. 141, 7 ( May 2016), 5-8. DOI=10.5120/ijca2016909633

@article{ 10.5120/ijca2016909633,
author = { Tasneem Mirza, Rishabh Indoria, Geet Dalwani, Krish Jain },
title = { Content based Image Retrieval using Color and Texture },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 141 },
number = { 7 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume141/number7/24794-2016909633/ },
doi = { 10.5120/ijca2016909633 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:42:48.432767+05:30
%A Tasneem Mirza
%A Rishabh Indoria
%A Geet Dalwani
%A Krish Jain
%T Content based Image Retrieval using Color and Texture
%J International Journal of Computer Applications
%@ 0975-8887
%V 141
%N 7
%P 5-8
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A Content Based Image Retrieval System is a computer system for browsing, searching and retrieving images from a large database of digital images .Most common methods of image retrieval utilize some method of adding meta data such as captioning, keywords or description to the images so that retrieval can be performed over the annotation words. Content Based Image Retrieval (CBIR) deals with retrieval of images based on visual features such as color, texture and shape. This paper presents retrieval of images based on color and texture using various proposed algorithms.

References
  1. Eakins, John; Graham,Margaret. “Content Based Image Retrieval” Northumbria at Newcastle. Retrieved 2014-03-10.
  2. J R Smith, “Integrated spatial and feature image system:Retrieval analysis and compression :[Ph D dissertation], Columbia University, New York, 1997.
  3. Rui Y, Huang T S, Chang S F. Image Retrieval: current techniques, promising directions and open issues, Journal of Visual Communication and Image Representation, 1999, 10(I): 39-62.
  4. Charles A. Poynton (2003). Digital Video and HDTV: Algorithms and Interfaces. Morgan Kaufmann. ISBN 1-55860-792-7.
  5. Nicholas Boughen (2003). Lightwave 3d 7.5 Lighting. Wordware Publishing, Inc.ISBN 1-55622-354-4.
  6. Bland, J.M.; Altman, D.G. (1996). "Statistics notes: measurementerror". BMJ 312(7047):1654. doi:10.1136/bmj.312.7047.1654. PMC 2351401. PMID 8664723.
  7. Pushpa B. Patil, Manesh B. Kokare, ”Relevance Feedback in Content Based Image Retrieval: A Review”, Journal of Applied Computer Science & Mathematics, no. 10(5) /2011, Suceava.
  8. P.S. Hiremath, JagdeeshPujari. “Content Based Image Retrieval based on Color, Texture and Shape features using Image and its complement” International Journal of Computer Science and Security, Volume (1): Issue (4).
Index Terms

Computer Science
Information Sciences

Keywords

Metadata Content Based Image Retrieval

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