We propose a polynomial-time algorithm for segmentation
and (open) boundary estimation which takes into account
a series of user-specified attraction points. In contrast
to existing algorithms which impose that the segmenting
boundary passes through these points, our algorithm allows
an imprecision in the user input. An energy minimization
approach imposes that the segmenting boundary optimally
passes along high-contrast edges in such a way that
at least one point along the computed boundary is as close
as possible to any given attraction point. In this sense, the
user input can be seen as a soft constraint. We prove that the
resulting optimization problem is NP-hard. We prove that in
the case that the user attraction points are ordered, then optimal
solutions can be computed in polynomial time using a
shortest path formulation in an appropriately constructed
four-dimensional graph spanned by the image pixels, a set
of tangent angles and the user attraction points. Expe...