@InProceedings{GenovezEbFrBeFrDu:2011:SeClIm,
               author = "Genovez, Patr{\'{\i}}cia Carneiro and Ebecken, Nelson Francisco 
                         Favilla and Freitas, Corina da Costa and Bentz, Cristina Maria and 
                         Freitas, Ramon Morais de and Dutra, Luciano Vieira",
          affiliation = "{Integrated Petroleum Expertise Company - IPEXco} and 
                         {Universidade Federal do Rio de Janeiro – UFRJ/COPPE} and 
                         {Instituto Nacional de Pesquisas Espaciais - INPE} and 
                         {PETROBRAS/CENPES - Centro de Pesquisas} and {Universidade Federal 
                         do Rio de Janeiro – UFRJ/COPP} and {Universidade Federal do Rio de 
                         Janeiro – UFRJ/COPP}",
                title = "Segmenta{\c{c}}{\~a}o e Classifica{\c{c}}{\~a}o de Imagens SAR 
                         Aplicadas {\`a} Detec{\c{c}}{\~a}o de Alvos Escuros em 
                         {\'A}reas Oce{\^a}nicas de Explora{\c{c}}{\~a}o e 
                         Produ{\c{c}}{\~a}o de Petr{\'o}leo",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "5973--5980",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "synthetic aperture radar (SAR), dark spot detection, oil 
                         detection, offshore exploration and production areas, image 
                         segmentation and clusterization, intelligent hybrid system, 
                         radares de abertura sint{\'e}tica (SAR), detec{\c{c}}{\~a}o de 
                         alvos escuros, detec{\c{c}}{\~a}o de {\'o}leo, 
                         explora{\c{c}}{\~a}o e produ{\c{c}}{\~a}o de petr{\'o}leo em 
                         {\'a}reas offshore, segmenta{\c{c}}{\~a}o e 
                         clusteriza{\c{c}}{\~a}o de imagens, sistema h{\'{\i}}brido 
                         inteligente.",
             abstract = "Automatic oil detection systems have been developed to improve SAR 
                         image interpretation, composed of four principal stages: a) image 
                         pre-processing; b) dark spot detection; c) feature extraction, 
                         and; d) oil and look-alike classification. The dark spot detection 
                         is considered the main step in the processing chain: without the 
                         geometry of the spots, the oil and look-alikes classification is 
                         unfeasible. In this context, this work aimed to develop an 
                         automatic procedure able to detect dark spots in SAR images, by 
                         the integration of segmentation and pattern recognition 
                         techniques. The results presented are continuity of the studies 
                         carried on by Genovez (2010) and consider the tree last stages as 
                         follow: a) features extraction, exploratory analyses and feature 
                         selection; b) dark spot detection using data clustering, and; c) 
                         validation of the proposed method. Considering that in the 
                         scientific community there isnt a wide agreement about the 
                         operational use of fully automatic methods, the development of an 
                         intelligent hybrid system, including decision rules able to 
                         conduct the images for one automatic or semi-automatic processing, 
                         was an interesting approach. The potential of these rules to 
                         improve the automation process was indicated. Nevertheless, more 
                         samples to return more robust rules are recommended in order to be 
                         widely applied to all SAR images acquired.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/39UL54P",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/39UL54P",
           targetfile = "p1570.pdf",
                 type = "Oceanografia e Gerenciamento Costeiro",
        urlaccessdate = "07 maio 2024"
}