Joint segmentation and registration of elastically deformable objects

Gilad Cohen, Joseph M. Francos, Rami Hagege

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

2 Scopus citations


We present a new approach to the general problem of template-based segmentation, detection, and registration. This joint problem is highly nonlinear and high dimensional, due to the large space of possible geometric transformations between a given template and its observed signature. Hence, any attempt to directly solve it inevitably leads to a high dimensional, nonlinear, non-convex optimization procedure. We propose a novel parametric solution to this problem, by showing that it can be equivalently represented by a low dimensional model, that is linear in the deformation parameters, and biased by the unknown observation background. Classical linear methods are then employed to estimate the deformation parameters, providing an explicit solution for the joint segmentation and registration problem.

Original languageEnglish
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)9781424421756
StatePublished - 1 Jan 2008

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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