Introduction This paper presents an active contour model to detect and segment objects in images whose boundaries may or may not be defined by their gradients. The curve evolution is based on the Mumford Shah energy functional and the level set methods, making it less susceptible to curve initialization errors. ...
Introduction This paper presents a generalized technique of matching a deformable model to an image through energy minimization. An active contour model called snakes has been proposed which is a continuous and deformable spline always minimizing its energy under the influence of image forces as well as internal energy of the spline and external constraint forces. Because of its dynamic nature, snakes can be applied to image segmentation tasks (edges, lines, and subjective contours) as well as to motion tracking and stereo matching. ...
Introduction This paper presents a stochastic active contour model for image segmentation from cardiac MR images. The proposed algorithms aims to minimize an energy functional by the level set method while incorporating stochastic region based and edge based information as well as shape priors of the heart and local contour properties. Moreover, the algorithm also uses a parameter annealing component to dynamically balance the weightage of the components of the energy functional. ...