Efficient numerical schemes for gradient vector flow

Authors:
Djamal Boukerroui
Affiliations:
Université de Technologie de Compiègne, CNRS, Heudiasyc, UMR, Centre de Recherche de Royallieu, Compiègne Cedex, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 10
Cited 2

Generalized gradient vector flow external forces for active contours

Signal Processing - Special issue on deformable models and techniques for image and signal processing
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiplicative Operator Splittings in Nonlinear Diffusion: From Spatial Splitting to Multiple Timesteps

Journal of Mathematical Imaging and Vision
Gradient Vector Flow Fast Geometric Active Contours

IEEE Transactions on Pattern Analysis and Machine Intelligence
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)

Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Integration of fuzzy spatial relations in deformable models-Application to brain MRI segmentation

Pattern Recognition
Snakes, shapes, and gradient vector flow

IEEE Transactions on Image Processing
Efficient and reliable schemes for nonlinear diffusion filtering

IEEE Transactions on Image Processing
Multigrid Geometric Active Contour Models

IEEE Transactions on Image Processing
Active Contour External Force Using Vector Field Convolution for Image Segmentation

IEEE Transactions on Image Processing

Efficient numerical schemes for gradient vector flow

Pattern Recognition
Fast gradient vector flow computation based on augmented Lagrangian method

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

Since its publication 10 years ago, the GVF has been used and adapted to various models and problems. Its popularity is certainly due to its effectiveness. The main drawback of GVF and its generalization, is their expensive computation load and its consequence on the capture range. We propose and compare in this work different efficient numerical schemes to solve the GVF and its generalizations.