A variational method for curve extraction with curvature-dependent energies
By: Majid Arthaud, Antonin Chambolle, Vincent Duval
Potential Business Impact:
Finds hidden lines and shapes in pictures.
We introduce a variational approach for extracting curves between a list of possible endpoints, based on the discretization of an energy and Smirnov's decomposition theorem for vector fields. It is used to design a bi-level minimization approach to automatically extract curves and 1D structures from an image, which is mostly unsupervised. We extend then the method to curvature-dependent energies, using a now classical lifting of the curves in the space of positions and orientations equipped with an appropriate sub-Riemanian or Finslerian metric.
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