A blur-invariant local feature for motion blurred image matching

Qiang Tong, Terumasa Aoki

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

Abstract

Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching.

Original languageEnglish
Title of host publicationNinth International Conference on Digital Image Processing, ICDIP 2017
EditorsXudong Jiang, Charles M. Falco
PublisherSPIE
ISBN (Electronic)9781510613041
DOIs
Publication statusPublished - 2017 Jan 1
Event9th International Conference on Digital Image Processing, ICDIP 2017 - Hong Kong, China
Duration: 2017 May 192017 May 22

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10420
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other9th International Conference on Digital Image Processing, ICDIP 2017
CountryChina
CityHong Kong
Period17/5/1917/5/22

Keywords

  • blur-invariant
  • descriptor
  • image matching
  • local feature
  • moment

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Tong, Q., & Aoki, T. (2017). A blur-invariant local feature for motion blurred image matching. In X. Jiang, & C. M. Falco (Eds.), Ninth International Conference on Digital Image Processing, ICDIP 2017 [104201E] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10420). SPIE. https://doi.org/10.1117/12.2281710