An unconditionally stable numerical method for bimodal image segmentation

DOI10.1016/j.amc.2012.09.038zbMath1309.65026OpenAlexW2149862726WikidataQ112880123 ScholiaQ112880123MaRDI QIDQ2018994

Yibao Li, Junseok Kim

Publication date: 26 March 2015

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2012.09.038

zbMATH Keywords

energy minimizationunconditional stabilityimage segmentationChan-Vese modelLee-Seo modellevel set model

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (8)

A compact fourth-order finite difference scheme for the three-dimensional Cahn-Hilliard equation ⋮ Deformable models for image segmentation: a critical review of achievements and future challenges ⋮ Effective document image binarization via a convex variational level set model ⋮ An unconditional stable compact fourth-order finite difference scheme for three dimensional Allen-Cahn equation ⋮ Radial basis functions and level set method for image segmentation using partial differential equation ⋮ Triply periodic minimal surface using a modified Allen-Cahn equation ⋮ The fractional Allen-Cahn equation with the sextic potential ⋮ Adaptive mesh refinement for simulation of thin film flows

Uses Software

• Matlab

Cites Work

• The application of resonance algorithm for image segmentation
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• A geometric model for active contours in image processing
• Geodesic active contours
• Semi-implicit finite volume scheme for image processing in 3D cylindrical geometry.
• Color image segmentation based on three levels of texture statistical evaluation
• Conformal curvature flows: from phase transitions to active vision
• A multiphase level set framework for image segmentation using the Mumford and Shah model
• Geometrical image segmentation by the Allen-Cahn equation
• Active contours driven by local Gaussian distribution fitting energy
• New numerical algorithms for the nonlinear diffusion model of image denoising and segmentation
• Threshold dynamics for the piecewise constant Mumford-Shah functional
• Globally optimal geodesic active contours
• An efficient local Chan-Vese model for image segmentation
• Optimal approximations by piecewise smooth functions and associated variational problems
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• A binary level set model and some applications to Mumford-Shah image segmentation
• Active contours without edges
• Mathematical problems in image processing. Partial differential equations and the calculus of variations. Foreword by Olivier Faugeras

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