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A Neutrosophic Image Retrieval Classifier

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
A. A. Salama, Mohamed Eisa, A. E. Fawzy
10.5120/ijca2017914798

A A Salama, Mohamed Eisa and A E Fawzy. A Neutrosophic Image Retrieval Classifier. International Journal of Computer Applications 170(9):1-6, July 2017. BibTeX

@article{10.5120/ijca2017914798,
	author = {A. A. Salama and Mohamed Eisa and A. E. Fawzy},
	title = {A Neutrosophic Image Retrieval Classifier},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {9},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {1-6},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume170/number9/28095-2017914798},
	doi = {10.5120/ijca2017914798},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

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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Keywords

Images in the Neutrosophic Domain, similarity measures, Euclidean distances.