Title :
Gradient vector flow fast geometric active contours
Author :
Paragios, Nikos ; Mellina-Gottardo, Olivier ; Ramesh, Visvanathan
Author_Institution :
Real-Time Vision & Modeling Dept., Siemens Corp. Res., Princeton, NJ, USA
fDate :
3/1/2004 12:00:00 AM
Abstract :
In this paper, we propose an edge-driven bidirectional geometric flow for boundary extraction. To this end, we combine the geodesic active contour flow and the gradient vector flow external force for snakes. The resulting motion equation is considered within a level set formulation, can deal with topological changes and important shape deformations. An efficient numerical schema is used for the flow implementation that exhibits robust behavior and has fast convergence rate. Promising results on real and synthetic images demonstrate the potentials of the flow.
Keywords :
differential geometry; edge detection; image segmentation; boundary extraction; convergence rate; edge driven bidirectional geometric flow; geodesic active contour flow; gradient vector flow; motion equation; shape deformation; synthetic images; topological changes; Active contours; Computer vision; Deformable models; Equations; Image segmentation; Lagrangian functions; Level set; Shape; Solid modeling; Topology; Algorithms; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2004.1262337