Distance maps and inscribed convex sets for shape classification applied to road signs
Frédérique Robert‐Inacio · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
This paper presents an algorithm enabling to detect disks on color images. The proposed method is based on a basic color segmentation giving a preliminary binary image. Then distance mapping is used to determine possible circles. And finally circle location is combined to color information in order to find the best-fitting disk. Furthermore, disks are, in a wide understanding, sets of points for which the distance to a particular point called center, is lower or equal to a given radius value. That is why the proposed method can also detect squares, octagons and other shapes that occur to be disks for a given distance, such as Euclidean, chessboard, Manhattan or chamfer distances. An application to pattern recognition for road sign interpretation is also presented in order to illustrate how road sign shape is a useful and significant information in the sign interpretation process.