Rain clouds tracking with radar image processing based on morphological skeleton matching

The aim of this study is to perform a short term forecasting of dynamic radar clutter evolution (shape and position). This dynamic clutter, like thunderstorms, can be tracked by means of adapted algorithms based on the matching of the morphological skeleton polygonal approximation by relaxation labeling processes. The efficiency of our methods is demonstrated on meteorological radar images. The objective of this application is dedicated to civil traffic regulation according to severe atmospheric phenomenon, as described in Monnier & al. (1997). Through radar environment assessment, we observe radar clutter, like precipitation, submitted to very complex deformations that cannot be modelized easily. In Barbaresco (1999), we proposed a method based on morphological skeleton deformation to forecast the fluid topological evolution. This method allows management of very complex shapes evolution thanks to polygonal approximation of the skeletons and matching of their closed couple of elements by the relaxation algorithm. The skeleton simplifies shape analysis and deformation but also distinguishes clutter displacement and articulated deformation by skeleton matching from homothetic deformation (inflation and deflation) by medial axis (radius of maximal disks contained in the shape) tracking