Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
International Journal of Computer Vision
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
A Variational Framework for Active and Adaptative Segmentation of Vector Valued Images
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours
International Journal of Computer Vision
International Journal of Computer Vision
IEEE Transactions on Image Processing
Brain MR Image Segmentation Using Local and Global Intensity Fitting Active Contours/Surfaces
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
International Journal of Computer Vision
Geodesically Linked Active Contours: Evolution Strategy Based on Minimal Paths
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Active contours driven by local Gaussian distribution fitting energy
Signal Processing
An efficient local Chan-Vese model for image segmentation
Pattern Recognition
Contrast Constrained Local Binary Fitting for Image Segmentation
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
The piecewise smooth Mumford-Shah functional on an arbitrary graph
IEEE Transactions on Image Processing
Γ-convergence approximation to piecewise smooth medical image segmentation
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
A brain MR image segmentation approach based on local intensity fitting curve evolution
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Integrating local distribution information with level set for boundary extraction
Journal of Visual Communication and Image Representation
Medical image segmentation based on novel local order energy
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Homogeneity- and density distance-driven active contours for medical image segmentation
Computers in Biology and Medicine
Level set segmentation based on local gaussian distribution fitting
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
A new level set method for inhomogeneous image segmentation
Image and Vision Computing
| Hi-index | 0.00 |
We propose a fast and robust segmentation model for piece-wise smooth images. Rather than modeling each region with global statistics, we introduce local statistics in an energy formulation. The shape gradient of this new functional gives a contour evolution controlled by local averaging of image intensities inside and outside the contour. To avoid the computational burden of a direct estimation, we express these terms as the result of convolutions. This makes an efficient implementation via recursive filters possible, and gives a complexity of the same order as methods based on global statistics. This approach leads to results similar to the general Mumford-Shah model but in a faster way, without solving a Poisson partial differential equation at each iteration. We apply it to synthetic and real data, and compare the results with the piecewise smooth and piecewise constant Mumford-Shah models.