@techreport{TR-IC-05-18,
  number = {IC-05-18},
  author = {A.X. Falcão and P.A.V. Miranda and A. Rocha and F.P.G. Bergo},
  title = {Object definition by kappa-connected components},
  month = {September},
  year = {2005}, 
  institution = {Institute of Computing, University of Campinas},
  note = {In English, 20 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       The notion of ``strength of connectedness'' between pixels has
       been successfully used in image segmentation. We present
       extensions to these works, which can considerably improve the
       efficiency of object definition tasks. A set of pixels is said
       a kappa-connected component with respect to a seed pixel, when
       the strength of connectedness of any pixel in that set with
       respect to the seed is higher than or equal to a threshold. We
       discuss two approaches that define objects based on
       kappa-connected components with respect to a given seed set:
       with and without competition among seeds. While the previous
       approaches either assume no competition with a single threshold
       for all seeds or eliminate the threshold for seed competition,
       we show that seeds with different thresholds can improve
       segmentation in both paradigms. We also propose automatic and
       user-friendly interactive methods to determining the
       thresholds. The proposed methods are presented in the framework
       of the image foresting transform, which naturally leads to
       efficient and correct graph algorithms. The improvements are
       demonstrated through several segmentation experiments involving
       medical images.
  }
}