Sub-Riemannian Fast Marching in SE(2)
Abstract
We propose a Fast Marching based implementation for computing sub-Riemanninan (SR) geodesics in the roto-translation group SE(2), with a metric depending on a cost induced by the image data. The key ingredient is a Riemannian approximation of the SR-metric. Then, a state of the art Fast Marching solver that is able to deal with extreme anisotropies is used to compute a SR-distance map as the solution of a corresponding eikonal equation. Subsequent backtracking on the distance map gives the geodesics. To validate the method, we consider the uniform cost case in which exact formulas for SR-geodesics are known and we show remarkable accuracy of the numerically computed SR-spheres. We also show a dramatic decrease in computational time with respect to a previous PDE-based iterative approach. Regarding image analysis applications, we show the potential of considering these data adaptive geodesics for a fully automated retinal vessel tree segmentation.
Keywords
Cite
@article{arxiv.1508.02553,
title = {Sub-Riemannian Fast Marching in SE(2)},
author = {Gonzalo Sanguinetti and Erik Bekkers and Remco Duits and Michiel Janssen and Alexey Mashtakov and Jean-Marie Mirebeau},
journal= {arXiv preprint arXiv:1508.02553},
year = {2015}
}
Comments
CIARP 2015