In recent years, the field of active contour-based image segmentation has s
een the emergence of two competing approaches. The first and oldest approac
h represents active contours in an explicit (or parametric) manner correspo
nding to the Lagrangian formulation. The second approach represents active
contours in an implicit manner corresponding to the Eulerian framework. Aft
er comparing these two approaches, we describe several new topological and
physical constraints applied to parametric active contours in order to comb
ine the advantages of these two contour representations. More precisely, we
introduce three algorithms related to the control of the contour topology,
geometry, and deformation. The first algorithm controls both vertex spacin
g and contour smoothness in an independent and intrinsic manner. The second
algorithm controls the contour resolution (number of vertices) while the t
hird algorithm automatically creates or fuses connected components on close
d or opened contours. The efficiency of these algorithms is demonstrated on
several images including medical images and a comparison with the level-se
ts method is also provided. (C) 2001 Academic Press.