Multiscale segmentation and approximation for significant description of 2D contours

This paper proposes a new approach for the multiscale segmentation and approximation of 2D contours. Its ultimate goal is to find the best set of constant curvature segments (straight line segments and/or circular arcs) to describe the contour in a way that respects its actual shape for recognition purposes. This approach is strictly based on discrete geometry principles, and the resulting algorithm named MuscaGrip (multiscale segmentation and contour approximation based on the geometry of regular inscribed polygons) computes, at multiple scales, two grouping processes