Vol. 34,  No. 8, pp. 772-781, Aug.  2009


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  Abstract

This paper proposes a novel algorithm for the efficient classification and retrieval of medical images. After color and edge features are extracted from medical images, these two feature vectors are then applied to a multi-class Support Vector Machine, to give membership vectors. Thereafter, the two membership vectors are combined into an ensemble feature vector. Also, to reduce the search time, Correlated Categories Vector is proposed for similarity matching. The experimental results show that the proposed system improves the retrieval performance when compared to other methods.

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  Cite this article

[IEEE Style]

K. Park, B. Ko, J. Nam, "," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 8, pp. 772-781, 2009. DOI: .

[ACM Style]

Ki-Hee Park, ByoungChul Ko, and Jae-Yeal Nam. 2009. . The Journal of Korean Institute of Communications and Information Sciences, 34, 8, (2009), 772-781. DOI: .

[KICS Style]

Ki-Hee Park, ByoungChul Ko, Jae-Yeal Nam, "," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 8, pp. 772-781, 8. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880