한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

  • 제34권8C호
  • /
  • Pages.772-781
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  • 2009
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  • 1226-4717(pISSN)
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  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지

Medical Image Retrieval based on Multi-class SVM and Correlated Categories Vector

  • 발행 : 2009.08.31
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초록

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.

키워드

참고문헌

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