Polar snakes: a fast and robust parametric active contour model

Authors:
Christophe Collewet
Affiliations:
INRIA Rennes-Bretagne Atlantique, IRISA, Lagadic team, Rennes, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 8
Cited 2

On active contour models and balloons

CVGIP: Image Understanding
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics

IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Modeling with Front Propagation: A Level Set Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Contours

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
Snakes, shapes, and gradient vector flow

IEEE Transactions on Image Processing
B-spline snakes: a flexible tool for parametric contour detection

IEEE Transactions on Image Processing
Robust real-time segmentation of images and videos using a smooth-spline snake-based algorithm

IEEE Transactions on Image Processing

An intensive restraint topology adaptive snake model and its application in tracking dynamic image sequence

Information Sciences: an International Journal
2-D ultrasound probe complete guidance by visual servoing using image moments

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present in this paper a way to perform a fast and robust image segmentation and to track a contour along a sequence of images. Our approach is based on a dynamic deformable model. More precisely, we revisit the physics based-model proposed in [1] to show the benefit of using a polar description to model the contour, in particular to cope with the well-known initialization problem. Indeed, we show that this way to proceed leads to diagonal and constant matrices in the equations of the snake evolution yielding therefore to a faster algorithm. Experimental results on image segmentation and contour tracking validate the efficiency of this new formulation.