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@InProceedings{MattosFerSilRivBra:2017:AsTeDe,
               author = "Mattos, Andrea Britto and Ferreira, Rodrigo S. and Silva, Reinaldo 
                         M. da Gama e and Riva, Mateus and Brazil, Emilio Vital",
          affiliation = "{IBM Research} and {IBM Research} and {IBM Research} and IME-USP 
                         and {IBM Research}",
                title = "Assessing Texture Descriptors for Seismic Image Retrieval",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "image retrieval, seismic.",
             abstract = "Much work has been done on the assessment of texture descriptors 
                         for image retrieval in many domains. In this work, we evaluate the 
                         accuracy and performance of three well-known texture descriptors 
                         -- Gabor Filters, GLCM, and LBP -- for seismic image retrieval. 
                         These subsurface images pose challenges yet not thoroughly 
                         investigated in previous works, which are addressed and evaluated 
                         in our experiments. We asked for domain experts to annotate two 
                         seismic cubes, Penobscot 3D and Netherlands F3, and used them to 
                         evaluate texture descriptors, corresponding parameters, and 
                         similarity metrics with the potential to retrieve visually similar 
                         regions of the considered datasets. While GLCM is used in the vast 
                         majority of works in this area, our findings indicate that LBP has 
                         the potential to produce satisfying results with lower 
                         computational cost.",
  conference-location = "Niter{\'o}i, RJ",
      conference-year = "Oct. 17-20, 2017",
             language = "en",
           targetfile = "Assessing Texture Descriptors for Seismic Image Retrieval.pdf",
        urlaccessdate = "2021, Jan. 19"
}


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