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A Study and Analysis on Feature Extraction in Content-Based Image Retrieval

Nadira T.1 , Rehna K.2 , Fepslin Athish Mon3

  1. Dept. of CSE, Royal College of Engineering and Technology, Thrissur, India.
  2. Dept. of CSE, Royal College of Engineering and Technology, Thrissur, India.
  3. Dept. of CSE, Royal College of Engineering and Technology, Thrissur, India.

Correspondence should be addressed to: nadira413@gmail.com.

Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-6 , Page no. 305-307, Jun-2017

Online published on Jun 30, 2017

Copyright © Nadira T., Rehna K., Fepslin Athish Mon . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Nadira T., Rehna K., Fepslin Athish Mon, “A Study and Analysis on Feature Extraction in Content-Based Image Retrieval,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.305-307, 2017.

MLA Style Citation: Nadira T., Rehna K., Fepslin Athish Mon "A Study and Analysis on Feature Extraction in Content-Based Image Retrieval." International Journal of Computer Sciences and Engineering 5.6 (2017): 305-307.

APA Style Citation: Nadira T., Rehna K., Fepslin Athish Mon, (2017). A Study and Analysis on Feature Extraction in Content-Based Image Retrieval. International Journal of Computer Sciences and Engineering, 5(6), 305-307.

BibTex Style Citation:
@article{T._2017,
author = {Nadira T., Rehna K., Fepslin Athish Mon},
title = {A Study and Analysis on Feature Extraction in Content-Based Image Retrieval},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2017},
volume = {5},
Issue = {6},
month = {6},
year = {2017},
issn = {2347-2693},
pages = {305-307},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1345},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1345
TI - A Study and Analysis on Feature Extraction in Content-Based Image Retrieval
T2 - International Journal of Computer Sciences and Engineering
AU - Nadira T., Rehna K., Fepslin Athish Mon
PY - 2017
DA - 2017/06/30
PB - IJCSE, Indore, INDIA
SP - 305-307
IS - 6
VL - 5
SN - 2347-2693
ER -

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Abstract

The digital image data is rapidly growing in quantity and heterogeneity. The existing information retrieval techniques does not meet the user’s demand, so there is need to develop an efficient system for content based image retrieval. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc... to search user required image from large annotated image database according to user`s requests, in the form of a query image. In this paper we present a study on some technical aspects of current content-based image retrieval systems and feature extraction. Features such as color, shape and texture are analysed to develop a high retrieval accurate cbir system.

Key-Words / Index Term

CBIR, visual database, texture, feature extraction, color correlogram

References

[1] D. A. Kumar and J. Esther, “Comparative Study on CBIR based by Color Histogram, Gabor and Wavelet Transform”, Int’l Journal of Computer Applications (0975 – 8887), vol. 17, no. 3, (2011) March, pp. 37.
[2] Khan,W., Kumar,S., Gupta,N., Khan,N., A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis, IJSCE, ISSN: 231-2307, Volume-I Issue-II,( May 2011).
[3] F. Long, H. J. Zhang and D. D. Feng, “Fundamentals of Content-based Image Retrieval, Multimedia Information Retrieval and Management”, D. Feng Eds, Springer, (2003).
[4] L. Haldurai and V. Vinodhini, "Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval", International Journal of Computer Sciences and Engineering, Vol.3, Issue.11, pp.11-15, 2015.
[5] L. Zheng, S. Wang, and Q. Tian, “Lp-norm IDF for scalable image ns. Image Process., vol. 23, no. 8, pp. 3604–3617, Aug. 2014