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@InProceedings{CarvalhoCostFerrCesa:2010:ImSeUs,
               author = "Carvalho, Marco Antonio Garcia de and Costa, Andre Luis Da and 
                         Ferreira, Anselmo Castelo Branco and Cesar Junior, Roberto 
                         Marcondes",
          affiliation = "Faculty of Technology-FT, University Of Campinas- UNICAMP and 
                         Faculty of Technology-FT, University Of Campinas- UNICAMP and 
                         Faculty of Technology-FT, University Of Campinas- UNICAMP and 
                         Department of Computer Science-IME, University Of Sao Paulo- USP",
                title = "Image Segmentation Using Component Tree and Normalized Cut",
            booktitle = "Proceedings...",
                 year = "2010",
               editor = "Bellon, Olga and Esperan{\c{c}}a, Claudio",
         organization = "Conference on Graphics, Patterns and Images, 23. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "image segmentation, component tree, watershed transform, graph 
                         partitioning, spectral graph.",
             abstract = "Graph partitioning, or graph cut, has been studied by several 
                         authors as a way of image segmenting. In the last years, the 
                         Normalized Cut has been widely used in order to implement graph 
                         partitioning, based on the graph spectra analysis (eigenvalues and 
                         eigenvectors). This area is known as Spectral Graph Theory. This 
                         work uses a hierarchical structure in order to represent images, 
                         the Component Tree. We provide image segmentation based on 
                         Normalized Cut, with image representation based on the Component 
                         Tree and on its scale-space analysis. Experimental results present 
                         a comparison between other image representations, as pixel grids, 
                         including multiscale graph decomposition formulation, and 
                         Watershed Transform. As the results show, the proposed approach, 
                         applied to different images, presents satisfying image 
                         segmentation.",
  conference-location = "Gramado",
      conference-year = "Aug. 30 - Sep. 3, 2010",
             language = "en",
           targetfile = "sibgrapi_article_2010.pdf",
        urlaccessdate = "2020, Nov. 25"
}


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