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文章基本信息

  • 标题:A Novel Optimized Image Feature Selection Algorithm Using Pairwise Classifiers
  • 本地全文:下载
  • 作者:Mahdi Bazarganigilani ; Ben Arko ; Ali Syed
  • 期刊名称:International Journal of Multimedia and Ubiquitous Engineering
  • 印刷版ISSN:1975-0080
  • 出版年度:2013
  • 卷号:8
  • 期号:1
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:Efficient Feature Selection; Content Based Image retrieval System; Pairwise Classifier
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