Presentation 2006/1/3
A SIMILAR IMAGE CLUSTERING METHOD INCLUDING AUTOMATIC SELECTION OF NUMBER OF CLUSTERS(International Workshop on Advanced Image Technology 2006)
Takatoshi Ohara, Takahiro Ogawa, Miki Haseyama, Hideo Kitajima,
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Abstract(in English) This paper proposes an image clustering method which includes an automatic cluster-number setting scheme. By using the proposed method, the user can effectively categorize similar images existing in an image database without presetting the total number of categories. Actually, the proposed method is based on a k-means algorithm which utilizes a color histogram of each image as a feature vector, and the number of the cluster is determined, according to the variation of the average of the clustering error in several number of the clusters. Consequently, the proposed method can automatically select the suitable number of the clusters for the image database, and then it provides the accurate image clustering result. Some experimental results show the proposed method achieves accurate clusterings.
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Paper # IE2005-223
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Committee IE
Conference Date 2006/1/3(1days)
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Registration To Image Engineering (IE)
Language ENG
Title (in Japanese) (See Japanese page)
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Title (in English) A SIMILAR IMAGE CLUSTERING METHOD INCLUDING AUTOMATIC SELECTION OF NUMBER OF CLUSTERS(International Workshop on Advanced Image Technology 2006)
Sub Title (in English)
Keyword(1)
1st Author's Name Takatoshi Ohara
1st Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name Takahiro Ogawa
2nd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
3rd Author's Name Miki Haseyama
3rd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
4th Author's Name Hideo Kitajima
4th Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
Date 2006/1/3
Paper # IE2005-223
Volume (vol) vol.105
Number (no) 501
Page pp.pp.-
#Pages 4
Date of Issue