Region-edge-based active contours driven by hybrid and local fuzzy region-based energy for image segmentation

DOI10.1016/J.INS.2020.08.078zbMath1475.68423OpenAlexW3082365061MaRDI QIDQ2055545

Jun Liu, Huaxiang Liu, He-Sheng Liu, Jiangxiong Fang, Liting Zhang

Publication date: 1 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.078

zbMATH Keywords

active contourintensity inhomogeneityedge energyhybrid energy

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (1)

Accurate image segmentation based on adaptive distance regularization level set method

Uses Software

• GitHub

Cites Work

• Global and local fuzzy energy-based active contours for image segmentation
• On local region models and a statistical interpretation of the piecewise smooth Mumford-Shah functional
• Active contours driven by local image fitting energy
• Geodesic active contours
• A variational model with hybrid images data fitting energies for segmentation of images with intensity inhomogeneity
• A novel active contour model for medical images via the Hessian matrix and eigenvalues
• A multiphase level set framework for image segmentation using the Mumford and Shah model
• An efficient local Chan-Vese model for image segmentation
• Optimal approximations by piecewise smooth functions and associated variational problems
• Active contours without edges
• Minimization of Region-Scalable Fitting Energy for Image Segmentation
• Fuzzy Energy-Based Active Contours
• Effective Level Set Image Segmentation With a Kernel Induced Data Term
• Distance Regularized Level Set Evolution and Its Application to Image Segmentation

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