An active contour model for image segmentation: A variational perspective

Abstract

Image segmentation is a crucial step in computer vision, medical imaging and image processing. There has been recently an interest in a nonlinear partial differential equation based approach, motivated by a more systematic approach for image segmentation. In this paper, a novel active contour model expressed in terms of an energy functional is formulated in a calculus of variations framework. The key idea behind the proposed technique is to segment objects from the background of images that may have non-uniform brightness because of illumination. Simulation results showing a much improved performance of the proposed method in image segmentation are analyzed and illustrated.