No abstract

We present a novel approach to parameterised curve detection. The method is based on the generalised Radon transform, which is traditionally applied to a 2D edge/line map. The novelty of our method is the mapping of the original 2D image to a 3D orientation space, which then forms the input for the Radon transform. The orientation space representation can represent multiple intersecting structures and contains local orientation information. We demonstrate our approach on a problem in geology and show that we can detect curves in a heterogeneous and noisy background.