Image Segmentation with a p-Laplace Equation Model

This paper presents a new model to image segmentation. We represent the object boundary by a partial differential equation model that is embedded in several scalar functions. The motion of the dynamic interface is governed by a p-Laplace equation. Such level set models are flexible in handling complex topological changes and are concise in extracting object boundaries despite of deep depression. Furthermore, a relatively smooth evolution can be maintained without re-initialization. The cost of this method is moderate. The accuracy and efficiency of the proposed algorithm are illustrated by several numerical examples.