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Reseach Article

CBIR using Textural Feature

by Nilam N Ghuge, Parul S Arora Bhalotra, B. D. Shinde
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 56 - Number 11
Year of Publication: 2012
Authors: Nilam N Ghuge, Parul S Arora Bhalotra, B. D. Shinde
10.5120/8937-3076

Nilam N Ghuge, Parul S Arora Bhalotra, B. D. Shinde . CBIR using Textural Feature. International Journal of Computer Applications. 56, 11 ( October 2012), 28-32. DOI=10.5120/8937-3076

@article{ 10.5120/8937-3076,
author = { Nilam N Ghuge, Parul S Arora Bhalotra, B. D. Shinde },
title = { CBIR using Textural Feature },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 56 },
number = { 11 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume56/number11/8937-3076/ },
doi = { 10.5120/8937-3076 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:58:35.609601+05:30
%A Nilam N Ghuge
%A Parul S Arora Bhalotra
%A B. D. Shinde
%T CBIR using Textural Feature
%J International Journal of Computer Applications
%@ 0975-8887
%V 56
%N 11
%P 28-32
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

CBIR system focuses on retrieving images from the database; the system depends on the way the indexing is being implemented. The way or method in which an image is stored will affect how it will be retrieved later and which can save more storage space and improve the retrieval process. Building effective content-based image retrieval (CBIR) systems involves the combination of image creation, storage, security, transmission, analysis, evaluation feature extraction, and feature combination in order to store and retrieve images effectively. The goal of CBIR systems is to support image retrieval based on content i. e. shape, color, texture. In this paper we have implemented CBIR techniques using conventional Histogram and Gabor filter. We have shown results of query image and retrieved image also 2D frequency response of Gabor filter with various angles as it is direction dependent filter. We have used Euclidean distance as a measure to calculate distance between two images.

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Index Terms

Computer Science
Information Sciences

Keywords

Content based Image retrieval Histogram Gabor function Euclidean distance Precision Recall