Image change detection algorithms: a systematic survey
Radke, R.J.
Andra, S.
Al-Kofahi, O.
Roysam, B.
Dept. of Electr., Rensselaer Polytech. Inst., Troy, NY, USA;
This paper appears in: Image Processing, IEEE Transactions on
Publication Date: March 2005
Volume: 14,
Issue: 3
On page(s): 294-307
ISSN: 1057-7149
INSPEC Accession Number: 8329220
Digital Object Identifier: 10.1109/TIP.2004.838698
Current Version Published: 2005-02-22
Abstract
Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.
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