@InProceedings{KortingFonsCama:2011:GeApSe,
               author = "Korting, Thales and Fonseca, Leila Maria Garcia and Camara, 
                         Gilberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "A Geographical Approach to Self-Organizing Maps Algorithm Applied 
                         to Image Segmentation",
            booktitle = "Proceedings...",
                 year = "2011",
               editor = "Blanc-Talon, J. et al.",
                pages = "162--170",
         organization = "Advanced Concepts for Intelligent Vision Systems.",
            publisher = "Springer-Verlag",
              address = "Berlin",
             abstract = "Image segmentation is one of the most challenging steps in image 
                         processing. Its results are used by many other tasks regarding 
                         information extraction from images. In remote sensing, 
                         segmentation generates regions according to found targets in a 
                         satellite image, like roofs, streets, trees, vegetation, 
                         agricultural crops, or deforested areas. Such regions 
                         differentiate land uses by classification algorithms. In this 
                         paper we investigate a way to perform segmentation using a 
                         strategy to classify and merge spectrally and spatially similar 
                         pixels. For this purpose we use a geographical extension of the 
                         Self-Organizing Maps (SOM) algorithm, which exploits the spatial 
                         correlation among near pixels. The neurons in the SOM will cluster 
                         the objects found in the image, and such objects will define the 
                         image segments.",
  conference-location = "Ghent, Belgica Berlin",
      conference-year = "2011",
                  doi = "10.1007/978-3-642-23687-7_15",
                  url = "http://dx.doi.org/10.1007/978-3-642-23687-7_15",
                label = "lattes: 0333390666972274 3 KortingFonsCama:2011:GeApSe",
             language = "en",
           targetfile = "korting2011geographical.pdf",
                  url = "http://www.dpi.inpe.br/gilberto",
               volume = "Lecture Notes in Computer Science, V. 6915",
        urlaccessdate = "11 maio 2024"
}