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Autonomous extraction of shape and topology of contours using geometry-driven diffusion and optimization of functionals

We show how geometry-driven diffusion based on the Nordstrom-functional can be used to crystallize the geometric content of a closed contour by simultaneously suppressing noise while enhancing the salient features. Furthermore, we propose a robust and highly parallelizable method that will automatically group edge-segments to produce a set of fully connected contours. The result could be used e.g., as input for recognition programs based on aspect graphs, or as a good initial guess for snakes and active contours.