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Deformable Model Using Radial Basis Functions Based Level Set Interpolation with an Ellipse Constraint

並列摘要


A level-set-based method using a radial basis functions (RBFs) based level set interpolation with an ellipse constraint is presented for image contour extraction. In the present method, the initial distance function embedded in the ellipse-constrained RBFs is interpolated using a coarse grid. The deformation of the level set function (LSF) is considered as an update of the RBFs' coefficients by solving an ordinary differential equation (ODE) and non-convex constrained quadratic programming (QCQP). A semi-definite relaxation approach is proposed to solve the non-convex QCQP problem. The proposed level set evolving scheme, which does not need initialization and re-initialization, is efficient and does not suffer from self-flattening. The objects with extremely complex shapes can be exactly fitted with a coarse grid of RBFs' centers and the image extraction is less sensitive to the distribution of the objects in the image domain.

參考文獻


Bernard, O.,Friboulet, D.,Thevenaz, P.,Unser, M.(2009).A variational b-spline level-set: A linear filtering approach for fast deformable model evolution.IEEE Trans. on Image Processing.18(6),1179-1191.
Casselles, V.,Kimmel, R.,Saprio, G.(1997).Geodesic active contours.International Journal of Computer Vision.22(1),61-79.
Chan, T.,Vese, L.(2001).Active contours without edges.IEEE Trans. on Image Processing.10(2),266-277.
Gelas, A.,Bernard, O.,Friboulet, D.,Prost, R.(2007).Compactly supported radial basis functions based collocation method for level-set evolution.IEEE Transactions on Image Processing.16(7),1873-1887.
Li, C.,Xu, C.,Gui, C.,Fox, M. D.(2010).Distance regularized level-set evolution and its application to image segmentation.IEEE Transactions on Image Processing.19(12),3243-3254.

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