Information fusion based on optical flow field and feature extraction for solving registration problems

Ze Xu Zhang*, Ping Yuan Cui

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel information fusion method for solving the automated registration problems was proposed. The main information sources include the global optical flow field and feature extracted from images. Our primary contribution is an improved estimation algorithm for computing the optical flow field using anisotropic diffusion. Moreover, we show that the registration process can be consolidated through the background registration and moving target registration that estimates global deformation while ensuring robustness to systematic errors such as those caused by moving foreground objects or occlusion. The validity and accuracy of the algorithm of optical flow on synthetic and real data are demonstrated. The simulation experiments for infrared images show that the fusion method is ideally suited for the application of automated image registration.

Original languageEnglish
Title of host publicationProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Pages4002-4007
Number of pages6
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 International Conference on Machine Learning and Cybernetics - Dalian, China
Duration: 13 Aug 200616 Aug 2006

Publication series

NameProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Volume2006

Conference

Conference2006 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityDalian
Period13/08/0616/08/06

Keywords

  • Automated registration
  • Feature extraction
  • Information fusion
  • Optical flow field

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