| Paper ID | SMR-3.10 | ||
| Paper Title | ACCURATE SILHOUETTE VECTORIZATION BY AFFINE SCALE-SPACE | ||
| Authors | Yuchen He, Sung Ha Kang, Georgia Institute of Technology, United States; Jean-Michel Morel, École Normale Supérieure Paris-Saclay, France | ||
| Session | SMR-3: Image and Video Representation | ||
| Location | Area F | ||
| Session Time: | Tuesday, 21 September, 15:30 - 17:00 | ||
| Presentation Time: | Tuesday, 21 September, 15:30 - 17:00 | ||
| Presentation | Poster | ||
| Topic | Image and Video Sensing, Modeling, and Representation: Image & video representation | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | Binary shapes, or silhouettes, are essential in human communication. They include, for example, all fonts and many logos. They can be extracted from images in raster form but require a vectorization for resolution independent editing. In this paper, we propose a mathematically founded silhouette vectorization algorithm, which converts a raster 2D shape to a Scalable Vector Graphics (SVG) format whose control points are geometrically stable under affine transformations. The proposed method can also be used as a reliable feature point detector for silhouettes. Compared to state-of-the-art graphics software, our algorithm shows a superior reduction in the number of control points for an equal or better accuracy. | ||