@techreport{TR-IC-04-11,
  number = {IC-04-11},
  author = {Ricardo da S. Torres and Alexandre X. Falcão},
  title = {Contour Salience Descriptors for Effective Image Retrieval
                  and Analysis},
  month = {October},
  year = {2004}, 
  institution = {Institute of Computing, University of Campinas},
  note = {In English, 20 pages.
    \par\selectlanguage{english}\textbf{Abstract}
        This work exploits the resemblance between content-based image
        retrieval and image analysis with respect to the design of
        image descriptors and their effectiveness. In this context,
        two shape descriptors are proposed: contour saliences and
        segment saliences. Contour saliences revisits its original
        definition, where the location of concave points was a
        problem, and provides a robust approach to incorporate concave
        saliences. Segment saliences introduces salience values for
        contour segments, making it possible to use an optimal
        matching algorithm as distance function. The proposed
        descriptors are compared with convex contour saliences,
        curvature scale space, and beam angle statistics using a fish
        database with 11,000 images organized in 1,100 distinct
        classes. The results indicate segment saliences as the most
        effective descriptor for this particular application and
        confirm the improvement of the contour salience descriptor in
        comparison with convex contour saliences.
  }
}