Presentation 2001/3/16
Acceleration of Image Retrieval by Filtering Based on Dimensionality Reduction and Clustering
Seiji HOTTA, Kohei INOUE, Kiichi URAHAMA,
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Abstract(in English) A filtering method is presented for acceleartion of image retrieval. The method exploits a lower-boundering property for distance based on dimensionality reduction of feature vectors and the triangle inequality. Images are clustered and retrieved on the basis of a quadratic form distance between color histograms. Database images are clustered by k-means method. This clustering is accelerated by filtering based on dimensionality reduction. Prototype images obtained by this clustering are utilized for kNN search of images. It is verified by experiments that the clustering is accelerated by dimensionality reduction and retrieval time is also reduced by filtering based on both of clustering and dimensionality reduction.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) image retrieval / filtering / dimension reduction / clustering
Paper # PRMU2000-235
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Conference Information
Committee PRMU
Conference Date 2001/3/16(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Acceleration of Image Retrieval by Filtering Based on Dimensionality Reduction and Clustering
Sub Title (in English)
Keyword(1) image retrieval
Keyword(2) filtering
Keyword(3) dimension reduction
Keyword(4) clustering
1st Author's Name Seiji HOTTA
1st Author's Affiliation Faculty of Visual Communication Design, Kyushu Institute of Design()
2nd Author's Name Kohei INOUE
2nd Author's Affiliation Faculty of Visual Communication Design, Kyushu Institute of Design
3rd Author's Name Kiichi URAHAMA
3rd Author's Affiliation Faculty of Visual Communication Design, Kyushu Institute of Design
Date 2001/3/16
Paper # PRMU2000-235
Volume (vol) vol.100
Number (no) 702
Page pp.pp.-
#Pages 6
Date of Issue