A Fast Level Set-Like Algorithm with Topology Preserving Constraint

Abstract

Implicit active contours are widely employed in image processing and related areas. Their implementation using the level set framework brings several advantages over parametric snakes. In particular, a parametrization independence, topological flexibility, and straightforward extension into higher dimensions have led to their popularity. However, in some applications the topological flexibility of the implicit contour is not desirable. Imposing topology-preserving constraints on evolving contours is often more convenient than including additional postprocessing steps. In this paper, we build on the work by Han et al. [1] introducing a topology-preserving extension of the narrow band algorithm involving simple point concept from digital geometry. In order to significantly increase computational speed, we integrate a fast level set-like algorithm by Nilsson and Heyden [2] with the simple point concept to obtain a fast topology-preserving algorithm for implicit active contours. The potential of the new algorithm is demonstrated on both synthetic and real image data.