Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
The nonconvex multi-dimensional Riemann problem for Hamilton-Jacobi equations
SIAM Journal on Mathematical Analysis
On active contour models and balloons
CVGIP: Image Understanding
High-order essentially nonsocillatory schemes for Hamilton-Jacobi equations
SIAM Journal on Numerical Analysis
Region-based strategies for active contour models
International Journal of Computer Vision
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical snakes: active region models
BMVC 94 Proceedings of the conference on British machine vision (vol. 2)
A level set formulation of Eulerian interface capturing methods for incompressible fluid flows
Journal of Computational Physics
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
A PDE-based fast local level set method
Journal of Computational Physics
Weighted ENO Schemes for Hamilton--Jacobi Equations
SIAM Journal on Scientific Computing
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Medical Image Segmentation via Coupled Curve Evolution Equations with Global Constraints
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Gradient Vector Flow Fast Geometric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Area and length minimizing flows for shape segmentation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Efficient energies and algorithms for parametric snakes
IEEE Transactions on Image Processing
Active contour model with gradient directional information: directional snake
IEEE Transactions on Circuits and Systems for Video Technology
A nonconservative flow field for robust variational image segmentation
IEEE Transactions on Image Processing
Gradient vector flow active contours with prior directional information
Pattern Recognition Letters
A multiresolution method for tagline detection and indexing
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
A geometric approach to the problem of reconstruction of the sample behavior in hidden dimensions
Pattern Recognition and Image Analysis
Variational nonlocal image segmentation using split-Bregman
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Information Sciences: an International Journal
Hi-index | 31.45 |
The task of image segmentation is to partition an image into non-overlapping regions based on intensity or textural reformation. The active contour methods provide an effective way for segmentation, in which the boundaries of the objects are detected by evolving curves. In this paper, we propose a new edge-based active contour method, which uses a long-range and orientation-dependent interaction between image boundaries and the moving curves while maintaining the edge fidelity. As a result, this method has a large capture range, and is able to detect sharp features of the images. The velocity field for the moving curves generated by this elastic interaction is calculated using the fast Fourier transform (FFT) method. Level set representation is used for the moving curves so that the topological changes during the evolution are handled automatically. This new method is derived based on the elastic interaction between line defects in solids (dislocations). Although it is derived originally for two dimensional segmentation, we also extend it to three dimensions. The features of the new method are examined by experiments on both synthetic images and medical images of blood vessels. Comparisons are made with the existing active contour methods.