Lamia Ben Youssef, Faouzi Ghorbel



The general principle of a matching algorithm is to optimize a criterion that furnishes a measure of the similarity between two images for a given space of geometrical transformations. In this work, we propose a framework based on a similarity measure – the generalized correlation – built in a systematic way from the links between a features space and a group of transformations modeled by an action group. Using results from representation theory, we can extend the correlation function to any homogeneous space with a transitively acting group. When the generalized Fourier transform exists, the group-based correlation can be expressed in a spectral space and it becomes possible to implement fast algorithms for its computation. Two important examples in the field of image processing are then detailed: the similarity group (rotation and scaling) on gray-level shapes from 2D images and the 3D rigid motion group (rotation and translation) followed by a plan projection.


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Paper Citation

in Harvard Style

Ben Youssef L. and Ghorbel F. (2006). IMAGE “GROUP-REGISTRATION” BASED ON REPRESENTATION THEORY . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 317-322. DOI: 10.5220/0001373903170322

in Bibtex Style

author={Lamia Ben Youssef and Faouzi Ghorbel},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},

in EndNote Style

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
SN - 972-8865-40-6
AU - Ben Youssef L.
AU - Ghorbel F.
PY - 2006
SP - 317
EP - 322
DO - 10.5220/0001373903170322