Image segmentation plays a crucial role in many applications where the identification of an object or of a portion of an image is relevant. Several approaches are available in the literature to set fast and reliable algorithms. We focus on a method based on the minimization of the Ambrosio-Tortorelli (AT) energy functional, customized in an image segmentation framework. To improve the efficiency of the method, we enrich the plain AT algorithm with anisotropic mesh adaptation.

This presentation is part of Minisymposium “MS30 - Imaging, Modeling, Visualization and Biomedical Computing (2 parts)”
organized by: Cristian Linte (Biomedical Engineering and Center for Imaging Science, Rochester Institute of Technology) , Suzanne Shontz (University of Kansas) .

Authors:

Simona Perotto (MOX, Politecnico di Milano)

Stefano Micheletti (MOX, Politecnico di Milano)

Alberto Silvio Chiappa (Politecnico di Milano)

Riccardo Peli (Politecnico di Milano)

Keywords:

image segmentation, partial differential equation models