@article{e9488c83533d419889b53ab91f02090b,
title = "A novel optimized image feature selection algorithm using pairwise classifiers",
abstract = "This paper introduces an optimized method to improve the accuracy of content based image retrieval systems (CBIR). CBIR systems classify the images according to low and higher features. This research improves both feature selection and classifier partition of a CBIR system. This paper normalizes and descretizes the feature vectors. A pair-wise classifier is employed to improve the accuracy of classification. Results show high accuracy of proposed classifier in an image database.",
keywords = "Open access version available, CBIR system, Content based image retrieval systems, Efficient feature selections, Feature vectors, Image database, Image features",
author = "Mahdi Bazarganigilani and Ben Arko and Ali Syed and Camille Price and Sandid Burki and Belinda Fridey and Michael Baron",
note = "Imported on 12 Apr 2017 - DigiTool details were: 086 FoR could not be migrated (XXX - XXX). month (773h) = January, 2013; Journal title (773t) = International Journal of Multimedia and Ubiquitous Engineering. ISSNs: 1975-0080; ",
year = "2013",
language = "English",
volume = "8",
pages = "107--116",
journal = "International Journal of Multimedia and Ubiquitous Engineering",
issn = "1975-0080",
publisher = "Science and Engineering Research Support Society",
number = "1",
}