@InProceedings{MachadoRodr:2016:FrDiSw,
               author = "Machado, Bruno Brandoli and Rodrigues Jr, Jose F",
          affiliation = "Instituto de Ci{\^e}ncias Matem{\'a}ticas e Computacional, 
                         Universidade de S{\~a}o Paulo and Instituto de Ci{\^e}ncias 
                         Matem{\'a}ticas e Computacional, Universidade de S{\~a}o Paulo",
                title = "Texture analysis using complex system models: fractal dimension, 
                         swarm systems and non-linear diffusion",
            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 = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "exture analysis, fractal dimension, swarm system, non-linear 
                         diffusion, complex networks.",
             abstract = "Texture is one of the primary visual attributes used to describe 
                         patterns found in nature. Several texture analysis methods have 
                         been used as powerful tools for real applications involving 
                         computer vision. However, existing methods do not successfully 
                         discriminate the complexity of texture patterns. Such methods 
                         disregard the possibility of describing image structures by 
                         fractal dimension. Fractality-based measures allow a non- integer 
                         geometric interpretation with applications in areas such as 
                         mathematics, physics, and biology. The central hypothesis of this 
                         work is that textures can be described as irregular fractal 
                         surfaces due to their complex geometry. Pushing the limits of the 
                         state-of-the-art, the results achieved in the four methodologies 
                         described in this work demonstrated the potential of using texture 
                         features in tasks of pattern recognition. The contributions of 
                         this work shall support significant advances in materials 
                         engineering, computer vision, and agriculture.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M9S8RS",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M9S8RS",
           targetfile = "article.pdf",
        urlaccessdate = "2024, Apr. 29"
}