Binary Shape Vectorization by Affine Scale-space

Yuchen He, Sung Ha Kang, Jean-Michel Morel

Abstract: Binary shapes, or silhouettes, are building elements of logos, graphic symbols and fonts， which require various forms of geometric editing without compromising the resolution. In this paper, we present an effective silhouette vectorization algorithm that extracts the outline of a 2D shape from a raster binary image and converts it to a combination of cubic Bézier polygons and perfect circles. Compared to state-of-the-art image vectorization software, this algorithm has demonstrated a superior reduction in the number of control points while maintaining high accuracy.