@techreport{TR-IC-05-19,
  number = {IC-05-19},
  author = {A.X. Falcão and P.A.V. Miranda and F.P.G. Bergo},
  title = {Automatic object detection by tree pruning},
  month = {September},
  year = {2005}, 
  institution = {Institute of Computing, University of Campinas},
  note = {In English, 24 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       The Image Foresting Transform (IFT) has been presented for the
       design of image processing operators based on connectivity. The
       IFT reduces image processing problems into a minimum-cost path
       forest problem in a graph derived from the image. In this paper
       we propose a new image operator, which solves segmentation by
       pruning trees of the forest. An IFT is applied to create a
       minimum-cost path forest whose roots are seed pixels, selected
       inside a desired object. In this forest, the background
       consists of a few subtrees rooted at pixels (leaking pointsq)
       on the object's boundary. The leaking pixels are identified and
       their subtrees are eliminated, such that the remaining forest
       defines the object. Tree pruning reduces image segmentation to
       the choice of a few pixels in the image, favoring solutions for
       automatic object detection. We present a user-friendly way of
       identifying leaking pixels and give solutions for their
       automatic detection. Since automatic seed selection may be
       different for each application, we evaluate automatic
       segmentation with tree pruning in three situations: labeling of
       multiple objects with similar textures, 3D object definition,
       and shape-based object detection. The results indicate that
       tree pruning is a promising approach to investigate automatic
       image segmentation.
  }
}