%0 Journal Article
%T Image Segmentation with Cage Active Contours
%A L.Garrido
%A M.Guerrieri
%A Laura Igual
%J IEEE Transactions on Image Processing
%D 2015
%V 24
%N 12
%@ 1057-7149
%F L.Garrido2015
%O MILAB
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2673), last updated on Wed, 14 Oct 2015 10:54:59 +0200
%X In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The parametrization, called mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. Our framework allows to easily formulate region-based energies to segment an image. In particular, we present three different local region-based energy terms: 1) the mean model; 2) the Gaussian model; 3) and the histogram model. We show the behavior of our method on synthetic and real images and compare the performance with state-of-the-art level set methods.
%K Level sets
%K Mean value coordinates
%K Parametrized active contours
%U http://dx.doi.org/10.1109/TIP.2015.2472298
%P 5557-5566