In this paper, for solving a class of shape optimization problems, a new algorithmic concept combining shape and topological sensitivities is presented. The geometry of interest is represented by means of geometrical implicit functions. While the topology optimization phase is based on a gradient descent scheme, the phase based on shape sensitivity uses Newton-type descent flows. The algorithm is applied to edge detector based image segmentation problems, but it can be extended to solve more general shape optimization problems as well.