A Variational Shape Optimization Approach for Image Segmentation with a Mumford–Shah Functional

DOI10.1137/070692066zbMath1195.49036OpenAlexW2007156453MaRDI QIDQ3648601

Pedro Morin, G. Doǧan, Ricardo H. Nochetto

Publication date: 27 November 2009

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/070692066

zbMATH Keywords

finite element methodshape optimizationimage segmentationMumford-Shah functionalimage smoothing

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Optimization of shapes other than minimal surfaces (49Q10) Algorithms for approximation of functions (65D15) Discrete approximations in optimal control (49M25) Machine vision and scene understanding (68T45) Mathematical programming (90C99)

Related Items (6)

Convergence analysis of variational and non-variational multigrid algorithms for the Laplace-Beltrami operator ⋮ Anisotropic mesh adaptation for region-based segmentation accounting for image spatial information ⋮ Segmentation of three-dimensional images with parametric active surfaces and topology changes ⋮ Fast Minimization of Region-Based Active Contours Using the Shape Hessian of the Energy ⋮ A hybrid variational front tracking-level set mesh generator for problems exhibiting large deformations and topological changes ⋮ Nonlinear Conjugate Gradient Methods for PDE Constrained Shape Optimization Based on Steklov--Poincaré-Type Metrics

Uses Software

• ALBERTA
• Triangle

This page was built for publication: A Variational Shape Optimization Approach for Image Segmentation with a Mumford–Shah Functional