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Reseach Article

A Neutrosophic Image Retrieval Classifier

by A. A. Salama, Mohamed Eisa, A. E. Fawzy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 170 - Number 9
Year of Publication: 2017
Authors: A. A. Salama, Mohamed Eisa, A. E. Fawzy

A. A. Salama, Mohamed Eisa, A. E. Fawzy . A Neutrosophic Image Retrieval Classifier. International Journal of Computer Applications. 170, 9 ( Jul 2017), 1-6. DOI=10.5120/ijca2017914798

@article{ 10.5120/ijca2017914798,
author = { A. A. Salama, Mohamed Eisa, A. E. Fawzy },
title = { A Neutrosophic Image Retrieval Classifier },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 170 },
number = { 9 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2017914798 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:17:59.904780+05:30
%A A. A. Salama
%A Mohamed Eisa
%A A. E. Fawzy
%T A Neutrosophic Image Retrieval Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 170
%N 9
%P 1-6
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

In this paper, we propose a two-phase Content-Based Retrieval System for images embedded in the Neutrosophic domain. In this first phase, we extract a set of features to represent the content of each image in the training database. In the second phase, a similarity measurement is used to determine the distance between the image under consideration (query image), and each image in the training database, using their feature vectors constructed in the first phase. Hence, the N most similar images are retrieved.

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Index Terms

Computer Science
Information Sciences


Images in the Neutrosophic Domain similarity measures Euclidean distances.