Supervised clustering algorithm based visual information features classification

Yuan Yuan; Nenghai Yu; Xuelong Li; Dacheng Tao; Zhengkai Liu

doi:10.1117/12.477206

Supervised clustering algorithm based visual information features classification

Yuan Yuan, Nenghai Yu, Xuelong Li, Dacheng Tao, Zhengkai Liu

University of Science and Technology of China

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

An intelligent image-indexing algorithm is proposed in this paper. It based on knowledge extracted from some simple single low-level image features. Two independent large image databases are built with more than 12000 images for training and test, and the experimental results show it work efficiently for high dimension database indexing. The running time is shorter than other algorithms proposed for the same purpose, and the algorithm performs even better for some certain semantic image classifications.

Original language	English
Pages (from-to)	614-618
Number of pages	5
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	4875
Issue number	1
DOIs	https://doi.org/10.1117/12.477206
State	Published - 2002
Externally published	Yes

Keywords

Image indexing
Machine learning
Normalization
Simple single feature

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10.1117/12.477206

Cite this

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abstract = "An intelligent image-indexing algorithm is proposed in this paper. It based on knowledge extracted from some simple single low-level image features. Two independent large image databases are built with more than 12000 images for training and test, and the experimental results show it work efficiently for high dimension database indexing. The running time is shorter than other algorithms proposed for the same purpose, and the algorithm performs even better for some certain semantic image classifications.",

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AU - Tao, Dacheng

AU - Liu, Zhengkai

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AB - An intelligent image-indexing algorithm is proposed in this paper. It based on knowledge extracted from some simple single low-level image features. Two independent large image databases are built with more than 12000 images for training and test, and the experimental results show it work efficiently for high dimension database indexing. The running time is shorter than other algorithms proposed for the same purpose, and the algorithm performs even better for some certain semantic image classifications.

KW - Image indexing

KW - Machine learning

KW - Normalization

KW - Simple single feature

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M3 - 文章

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Supervised clustering algorithm based visual information features classification

Abstract

Keywords

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