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

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Abstract

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.

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Acknowledgement

This research was supported by the MKE (Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-C1090-1001-0008)

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Authors and Affiliations

  1. Department of Electrical Engineering, Korea University, Seoul, Republic of Korea

    Yoon-Sik Tak, Seungmin Rho & Eenjun Hwang

  2. Division of Internet & Multimedia Engineering, Konkuk University, Seoul, Republic of Korea

    Hanku Lee

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  1. Yoon-Sik Tak
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  2. Seungmin Rho
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  3. Eenjun Hwang
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  4. Hanku Lee
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Correspondence to Eenjun Hwang.

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Tak, YS., Rho, S., Hwang, E. et al. Tertiary hash tree-based index structure for high dimensional multimedia data. Multimed Tools Appl 61, 51–68 (2012). https://doi.org/10.1007/s11042-010-0687-8

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  • DOI: https://doi.org/10.1007/s11042-010-0687-8

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