Tertiary hash tree: Indexing structure for content-based image retrieval

Yoon Sik Tak, Eenjun Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Dominant features for content-based image retrieval usually consist of high-dimensional values. So far, many researches have been done to index such values for 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 result 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 values. 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
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages3167-3170
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 2010 Aug 232010 Aug 26

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other2010 20th International Conference on Pattern Recognition, ICPR 2010
CountryTurkey
CityIstanbul
Period10/8/2310/8/26

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Tak, Y. S., & Hwang, E. (2010). Tertiary hash tree: Indexing structure for content-based image retrieval. In Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010 (pp. 3167-3170). [5597176] (Proceedings - International Conference on Pattern Recognition). https://doi.org/10.1109/ICPR.2010.775