A novel and blur-invariant local feature image matching

Qiang Tong, Terumasa Aoki

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

Abstract

The lack of robustness to blur (especially motion blur) is one of the biggest problem in the existing local feature schemes. In this paper, we present a novel Local feature scheme to solve this problem. Our proposed method is good at image matching between (motion and Gaussian) blurred images and non-blurred images. Experimental results show that the proposed method outperforms state of the art methods for blurred image matching.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-60
Number of pages2
ISBN (Electronic)9781509040179
DOIs
Publication statusPublished - 2017 Jul 25
Event4th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017 - Taipei, United States
Duration: 2017 Jun 122017 Jun 14

Publication series

Name2017 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017

Other

Other4th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2017
CountryUnited States
CityTaipei
Period17/6/1217/6/14

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Signal Processing
  • Biomedical Engineering
  • Instrumentation
  • Electrical and Electronic Engineering

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