An integral active contour model for convex hull and boundary extraction

Abstract

This paper presents a new deformable model capable of segmenting images with multiple complex objects and deep concavities. The method integrates a shell algorithm, an active contour model and two active convex hull models. The shell algorithm automatically inscribes every image object into a single convex curve. Every curve is evolved to the boundary's vicinity by the exact solution of a specific form of the heat equation. Further, if re-parametrization is applied at every time step of the evolution the active contour will converge to deep concavities. But if distance function minimization or line equation is used to stop the evolution, the active contour will define the convex hull of the object. Set of experiments are performed to validate the theory. The contributions, the advantages and bottlenecks of the model are underlined at the end by a comparison against other methods in the field. © 2009 Springer-Verlag.