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Content-based Image Retrieval (CBIR) using Hybrid Technique

by Zainab Ibrahim Abood, Israa Jameel Muhsin, Nabeel Jameel Tawfiq
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 12
Year of Publication: 2013
Authors: Zainab Ibrahim Abood, Israa Jameel Muhsin, Nabeel Jameel Tawfiq
10.5120/14500-2307

Zainab Ibrahim Abood, Israa Jameel Muhsin, Nabeel Jameel Tawfiq . Content-based Image Retrieval (CBIR) using Hybrid Technique. International Journal of Computer Applications. 83, 12 ( December 2013), 17-24. DOI=10.5120/14500-2307

@article{ 10.5120/14500-2307,
author = { Zainab Ibrahim Abood, Israa Jameel Muhsin, Nabeel Jameel Tawfiq },
title = { Content-based Image Retrieval (CBIR) using Hybrid Technique },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 12 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number12/14500-2307/ },
doi = { 10.5120/14500-2307 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:59:10.980461+05:30
%A Zainab Ibrahim Abood
%A Israa Jameel Muhsin
%A Nabeel Jameel Tawfiq
%T Content-based Image Retrieval (CBIR) using Hybrid Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 12
%P 17-24
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co-occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is concluded that, for the database images used in this work, the CBIR using hybrid technique is better for image retrieval because it has a higher match performance (100%) for each type of similarity measure so; it is the best one for image retrieval.

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Index Terms

Computer Science
Information Sciences

Keywords

CBIR feature extraction properties color histogram GLCM hybrid similarity measure.

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