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@InProceedings{RittnerFlorLotu:2007:TeMoGr,
               author = "Rittner, Leticia and Flores, Franklin and Lotufo, Roberto",
          affiliation = "{Faculdade de Engenharia El{\'e}trica e de Computa{\c{c}}{\~a}o 
                         - UNICAMP} and {Faculdade de Engenharia El{\'e}trica e de 
                         Computa{\c{c}}{\~a}o - UNICAMP} and {Faculdade de Engenharia 
                         El{\'e}trica e de Computa{\c{c}}{\~a}o - UNICAMP}",
                title = "New tensorial representation of color images: tensorial 
                         morphological gradient applied to color image segmentation",
            booktitle = "Proceedings...",
                 year = "2007",
               editor = "Falc{\~a}o, Alexandre Xavier and Lopes, H{\'e}lio C{\^o}rtes 
                         Vieira",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 20. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "color image segmentation, color gradient, watershed transform.",
             abstract = "This paper proposes a new Tensorial Representation of HSI color 
                         images, where each pixel is a 2 X 2 second order tensor, that can 
                         be represented by an ellipse. A proposed tensorial morphological 
                         gradient (TMG) is defined as the maximum dissimilarity over the 
                         neighborhood determined by a structuring element, and is used in 
                         the watershed segmentation framework. Many tensor dissimilarity 
                         functions are tested and other color gradients are compared. The 
                         comparison uses a new methodology for qualitative evaluation of 
                         color image segmentation by watershed, where the watershed lines 
                         of the n most significant regions are overlaid on the original 
                         image for visual comparison. Experiments show that the TMG using 
                         Frobenius norm dissimilarity function presents superior 
                         segmentation results, in comparison to other tested gradients.",
  conference-location = "Belo Horizonte",
      conference-year = "Oct. 7-10, 2007",
             language = "en",
           targetfile = "rittner-tensor.pdf",
        urlaccessdate = "2020, Oct. 26"
}


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