Tertiary hash tree-based index structure for high dimensional multimedia data

Dominant features for the content-based image retrieval usually have high-dimensionality. So far, many researches have been done to index such values to support fast retrieval. Still, many existing indexing schemes are suffering from performance degradation due to the curse of dimensionality problem...

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Bibliographic Details
Published in:Multimedia tools and applications 2012-11, Vol.61 (1), p.51-68
Main Authors: Tak, Yoon-Sik, Rho, Seungmin, Hwang, Eenjun, Lee, Hanku
Format: Article
Language:English
Subjects:
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Multimedia Information Systems
Special Purpose and Application-Based Systems
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Summary:Dominant features for the content-based image retrieval usually have high-dimensionality. So far, many researches have been done to index such values to support fast retrieval. Still, many existing indexing schemes are suffering from performance degradation due to the curse of dimensionality problem. As an alternative, heuristic algorithms have been proposed to calculate the answer with ‘high probability’ at the cost of accuracy. In this paper, we propose a new hash tree-based indexing structure called tertiary hash tree for indexing high-dimensional feature data. Tertiary hash tree provides several advantages compared to the traditional extendible hash structure in terms of resource usage and search performance. Through extensive experiments, we show that our proposed index structure achieves outstanding performance.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-010-0687-8