  Starting from a variational formulation, we present a model for image
segmentation that employs both region statistics and edge information. This
combination allows for improved flexibility, making the proposed model suitable
to process a wider class of images than purely region-based and edge-based
models. We perform several simulations with real images that attest to the
versatility of the model. We also show another set of experiments on images
with certain pathologies that suggest opportunities for improvement.
