Abstract: An image segmentation model based on the view of
Riemannian Geometry was proposed. Endowed with a Riemannian metric
derived from the gray scale information of a given image, the image
space became a Riemannian manifold. On this Riemannian manifold, we
evolved a curve by the mean curvature flow using the level set
methods. Because the gray scale information had been embedded into
the Riemannian manifold, the evolution was intrinsic. Calculations
show that the method is an extension of existing models;
furthermore, finer controls for the evolution can be achieved.
Numerical experiments show the effectivity and some good features of
the proposed method.

Key words: segmentation, riemannian metric, level set methods, image processing, segmentation, riemannian metric, level set methods