Gabor-Space Geodesic Active Contours

A novel scheme for texture segmentation is presented. Our algorithm is based on generalizing the intensity-based geodesic active contours model to the Gabor spatial-feature space of images. First, we apply the Gabor-Morlet transform to the image using self similar Gabor functions, and then implement the geodesic active snakes mechanism in this space. The spatial-feature space is represented, via the Beltrami framework, as a Riemannian manifold. The stopping term, in the geodesic snake mechanism, is generalized and is derived from the metric of the Gabor spatial-feature manifold. Experimental results obtained by applying the scheme to test images are presented