Tracking Meteorological Structures Through Curve Matching Using Geodesic Paths

This paper is concerned with the problem of tracking clouds structures like vortices in meteorological images. For this purpose we characterize the deformation between two successive occurrences, by matching their two boundary curves. Our approach is based on the computation of the set of paths connecting the two curves to be matched. It minimizes a cost function which measures the local similarity of the two curves. These matching paths are obtained as geodesic curves on this cost surface. Moreover our method allows to consider complex curves of arbitrary topology since these curves are represented through an implicit function rather than through a parameterization. Experimental results are given to illustrate the properties of the method in processing synthetic and then meteorologic remotely-sensed data. Key-words: Curves matching, Image sequence analysis, Geodesic distance computation, Eulerian formulation.