Co-volume method for Riemannian mean curvature flow in subjective surfaces multiscale segmentation

  • Authors:

  • Karol Mikula;Alessandro Sarti;Fiorella Sgallari

  • Affiliations:

  • Department of Mathematics, Slovak University of Technology, Radlinského 11, 813 68, Bratislava, Slovakia;DEIS, University of Bologna, Via Risorgimento 2, 40136, Bologna, Italy;Department of Mathematics, University of Bologna, Piazza di Porta S. Donato 5, 40127, Bologna, Italy

  • Venue:
  • Computing and Visualization in Science
  • Year:
  • 2006

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Abstract

We introduce semi-implicit complementary volume numerical scheme for solving the level setformulation of Riemannian mean curvature flow problem arising in image segmentation, edge detection, missing boundary completion and subjective contour extraction. The scheme is robust and efficient since it is linear, and it is stable in L_∞ and weighted W 1,1 sense without any restriction on a time step. The computational results related to medical image segmentation with partly missing boundaries and subjective contours extraction are presented.