Optimized image feature selection using pairwise classifiers

• Autorzy: Bazarganigilani M.
• Języki publikacji: EN

Abstrakty

EN

In this paper, we introduce 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.In our research, we improve both feature selection and classifier partition of a CBIR system. Results show great performance of our proposed algorithm.

Słowa kluczowe

EN

content based image retrieval systems; content-based image retrieval (CBIR); higher feature; classifier

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2011
• Tom: Vol. 1, No. 2
• Strony: 147--153
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Bazarganigilani M.

• Charles Sturt University Faculty of Business, Melbourne, Australia

Bibliografia

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