An efficient and provably correct algorithm for the multiscale estimation of image contours by means of polygonal lines

Abstract

A large portion of image contours is characterized by local properties such as sharp variations of the image intensity across the contour. The integration of local image descriptors estimated by using these local properties into curvilinear descriptors is a difficult problem from a theoretical viewpoint because of the combinatorially large number of possible curvilinear descriptors. To deal with this difficulty, the notion of compressible graphs is introduced and a contour data model is defined leading to an efficient linear-time algorithm which provably recovers contours with an upper bound on the approximation error.