An efficient algorithm for point matching using hilbert scanning distance

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Abstract

A fast and accurate similarity named Hilbert Scanning Distance(HSD) [9] has recently been presented for point matching. In this study, we improved an efficient algorithm of search strategy for HSD in the large search space. This search strategy is associated with two ideas: a relaxation greedy search, and an accelerating process using Monte Carlo sampling. The experimental results implicate that this improved algorithm is robust and efficient for point matching using HSD. It also makes a tradeoff between accuracy and speed under different requirements.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages873-876
Number of pages4
Volume3
DOIs
Publication statusPublished - 2006
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong
Duration: 2006 Aug 202006 Aug 24

Other

Other18th International Conference on Pattern Recognition, ICPR 2006
CityHong Kong
Period06/8/2006/8/24

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

Cite this

Tian, L., & Kamata, S. (2006). An efficient algorithm for point matching using hilbert scanning distance. In Proceedings - International Conference on Pattern Recognition (Vol. 3, pp. 873-876). [1699664] https://doi.org/10.1109/ICPR.2006.237