2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. (2003)
June 18, 2003 to June 20, 2003
Andrea Torsello , University of York
Edwin R. Hancock , University of York
The Hamilton-Jacobi approach has proved to be a powerful and elegant method for extracting the skeleton of a shape. The approach is based on the fact that the inward evolving boundary flux is conservative everywhere except at skeletal points. Nonetheless this method appears to overlook the fact that the linear density of the evolving boundary front is not constant where the front is curved. In this paper we present an analysis which takes into account variations of density due to boundary curvature. This yields a skeletonization algorithm that is both better localized and less susceptible to boundary noise than the Hamilton-Jacobi method.
A. Torsello and E. R. Hancock, "Curvature Correction of the Hamilton-Jacobi Skeleton," 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.(CVPR), Madison, Wisconsin, 2003, pp. 828.