In this paper a new image segmentation model based on techniques of curve evolution

piecewise smooth Mumford Shah functional for segmentation and level sets was proposed as improvement of C V method. New method shows global optimization and less insensibility of initialization and can detect objects whose boundaries are not necessarily defined by gradient and solves the problem of locating the edges on images with non uniform brightness

for which the previous methods based on piecewise constant Mumford Shah model

including the C V method

are not applicable. Besides

the model was improved for the location of subtle and complicated edges of target objects by the modification of PDE. In order to further stabilize and fasten the level set evolution procedures

the paper addresses an improved approach to construction of the signed distance function using new Voronoi source scanning method

which needs simple comparison and few multiplication operations

faster than the traditional approaches. Finally

various experimental results for synthesized and real images will be presented to prove the proposed model efficiency and stabilized.