@InProceedings{FrutuosoGomSanCavVid:2016:TeAnUs,
               author = "Frutuoso, Romulo Lopes and Gomes, Joao Paulo P. and Santos, 
                         Emanuele M. dos and Cavalcante Neto, Joaquim B. and Vidal, Creto 
                         A.",
          affiliation = "Department of Computer Science, Universidade Federal do Ceara - 
                         UFC and Department of Computer Science, Universidade Federal do 
                         Ceara - UFC and Department of Computer Science, Universidade 
                         Federal do Ceara - UFC and Department of Computer Science, 
                         Universidade Federal do Ceara - UFC and Department of Computer 
                         Science, Universidade Federal do Ceara - UFC",
                title = "Texture Analysis using Informed Search in Graphs",
            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 = "pattern recognition, texture analysis, search methods, informed 
                         search.",
             abstract = "In this paper we propose a variant oisf the TASPG algorithm for 
                         texture recognition. TASPG (Texture Analysis based on Shortest 
                         Paths in Graphs) is a recently proposed texture recognition method 
                         that extracts features from paths along texture images. Although 
                         TASPG achieved promising results, its application may be limited 
                         by its high computational cost which stems from the extensive use 
                         of Dijkstra's algorithm. In this work, we propose a variant of 
                         TASPG, called TAISG, that uses an informed search algorithm to 
                         reduce the number of visited nodes in the search procedure. The 
                         proposed method was compared with TASPG and other texture 
                         classification methods and showed good results, both in 
                         recognition rate and in computational cost.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.057",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.057",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M4UNHT",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M4UNHT",
           targetfile = "PID4364901.pdf",
        urlaccessdate = "2024, Apr. 29"
}