PT Journal
AU Oriol Pujol
   Debora Gil
   Petia Radeva
TI Fundamentals of Stop and Go active models
SO Image and Vision Computing
PY 2005
BP 681
EP 691
VL 23
IS 8
DI 10.1016/j.imavis.2005.03.007
DE Deformable models; Geodesic snakes; Region-based segmentation
AB An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation.
PI Newton, MA, USA
ER