author = "Mansilla, Lucy A. C. and Miranda, Paulo A. V.",
          affiliation = "Department of Computer Science, University of S{\~a}o Paulo (USP) 
                         and Department of Computer Science, University of S{\~a}o Paulo 
                title = "Oriented Image Foresting Transform Segmentation: Connectivity 
                         Constraints with Adjustable Width",
            booktitle = "Proceedings...",
                 year = "2016",
               editor = "Aliaga, Daniel G. and Davis, Larry S. and Farias, Ricardo C. and 
                         Fernandes, Leandro A. F. and Gibson, Stuart J. and Giraldi, Gilson 
                         A. and Gois, Jo{\~a}o Paulo and Maciel, Anderson and Menotti, 
                         David and Miranda, Paulo A. V. and Musse, Soraia and Namikawa, 
                         Laercio and Pamplona, Mauricio and Papa, Jo{\~a}o Paulo and 
                         Santos, Jefersson dos and Schwartz, William Robson and Thomaz, 
                         Carlos E.",
         organization = "Conference on Graphics, Patterns and Images, 29. (SIBGRAPI)",
            publisher = "IEEE Computer Society´s Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "image segmentation, connectivity constraints, boundary polarity, 
                         image foresting transform.",
             abstract = "In this work, we extend a novel seed-based segmentation algorithm, 
                         which provides global optimum solutions according to a graph-cut 
                         measure, subject to high-level boundary constraints: The 
                         simultaneously handling of boundary polarity and connectivity 
                         constraints. The proposed method incorporates the connectivity 
                         constraint in the Oriented Image Foresting Transform (OIFT), 
                         ensuring the generation of connected objects, but such that the 
                         connection between its internal seeds is guaranteed to have a 
                         user-controllable minimum width. In other frameworks, such as the 
                         min-cut/max-flow algorithm, the connectivity constraint is known 
                         to lead to NP-hard problems. In contrast, our method conserves the 
                         low complexity of the OIFT algorithm. In the experiments, we show 
                         improved results for the segmentation of thin and elongated 
                         objects, for the same amount of user interaction. Our dataset of 
                         natural images with true segmentation is publicly available to the 
  conference-location = "S{\~a}o Jos{\'e} dos Campos",
      conference-year = "Oct. 4-7, 2016",
                  doi = "10.1109/SIBGRAPI.2016.047",
                  url = "",
             language = "en",
           targetfile = "PID4359641.pdf",
        urlaccessdate = "2021, Jan. 27"