PT Journal
AU L.Garrido
   M.Guerrieri
   Laura Igual
TI Image Segmentation with Cage Active Contours
SO IEEE Transactions on Image Processing
JI TIP
PY 2015
BP 5557
EP 5566
VL 24
IS 12
DI 10.1109/TIP.2015.2472298
DE Level sets; Mean value coordinates; Parametrized active contours
AB 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.
ER