DEFORMABLE MODEL USING RADIAL BASIS FUNCTIONS BASED LEVEL SET INTERPOLATION WITH AN ELLIPSE CONSTRAINT
DOI:
https://doi.org/10.7903/ijecs.1350Keywords:
Image Segmentation, Level Set Interpolation, Radial Basis Functions, Deformable Model, Constrained Quadratic ProgrammingAbstract
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.
To cite this document: Hoang-Nam Nguyen, Pi-Ying Cheng, and Tai-Yan Kam, "Deformable model using radial basis functions based level set interpolation with an ellipse constraint", International Journal of Electronic Commerce Studies, Vol.5, No.2, pp. 247-256, 2014.
Permanent link to this document:
http://dx.doi.org/10.7903/ijecs.1350
