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Reseach Article

Analytical Study of CBIR Techniques

Published on July 2015 by M.y.patil, C.a. Dhawale
National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
Foundation of Computer Science USA
NCKITE2015 - Number 2
July 2015
Authors: M.y.patil, C.a. Dhawale

M.y.patil, C.a. Dhawale . Analytical Study of CBIR Techniques. National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). NCKITE2015, 2 (July 2015), 31-36.

author = { M.y.patil, C.a. Dhawale },
title = { Analytical Study of CBIR Techniques },
journal = { National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) },
issue_date = { July 2015 },
volume = { NCKITE2015 },
number = { 2 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 31-36 },
numpages = 6,
url = { /proceedings/nckite2015/number2/21488-2657/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%A M.y.patil
%A C.a. Dhawale
%T Analytical Study of CBIR Techniques
%J National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%@ 0975-8887
%N 2
%P 31-36
%D 2015
%I International Journal of Computer Applications

Content based Image retrieval (CBIR) means search the contents of the image instead of information and capture images from database as per the user requirement. Content refers to as color, shapes, textures or any other information. The image retrieval is interesting and fastest developing methodology in all fields. It iseffective and well-organized approach for retrieving the image from large scale database. CBIR is a technique to take input as query object and gives output from an image database. To build up content based image retrieval system, to improve various processes implicated in retrieval like feature extraction, Image retrieval and similarity matching techniques. In this paper surveys has been conducted on some features such as color, texture and shape retrieval of images from the database and also study to compared content based image retrieval features like Color, texture and shape for efficient and accurate image retrieval. After going through exhaustive analysis of these CBIR techniques there isvarious parameters to review the paper, some of them it is found that each technique have its own strengths and limitations. So this paper gives summarization of the different features of images with their functionality for content based image retrieval systems.

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Index Terms

Computer Science
Information Sciences


Cbir feature Extraction Color Shape And Textures