A variational framework for multi-region image segmentation based on image structure tensor

Abstract

This paper presents a variational framework for multi-region image segmentation method based on image structure tensor. The multi-region segmentation is addressed by employing the multiphase level set functions with constraint. The image feature is extracted by using the image structure tensor. The coupled Partial Differential Equations (PDE) related to the minimization of the functional are considered through a dynamical scheme. A modified region competition factor is adopted to speed up the cure evolution functions, it also guarantees no vacuum and non-overlapping between the neighbor regions. Several experiments are conducted on both synthetic images and natural image. The results illustrate that the proposed multi-region segmentation method is fast and less sensitive to the initializations. © Springer-Verlag Berlin Heidelberg 2013.