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

Yoon Sik Tak, Seungmin Rho, Eenjun Hwang, Hanku Lee

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)51-68
Number of pages18
JournalMultimedia Tools and Applications
Issue number1
Publication statusPublished - 2012 Nov

Bibliographical note

Funding Information:
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)


  • Content-based
  • Extendible hash
  • Image retrieval
  • Multi-dimensional data
  • Tertiary hash tree

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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