@InProceedings{FreitasGoMaSaBoPi:2016:UsCoFi,
               author = "Freitas, Ueliton and Gon{\c{c}}alves, Wesley Nunes and Matsubara, 
                         Edson Takashi and Sabino, Jose and Borth, Marcelo Rafael and 
                         Pistori, Hemerson",
          affiliation = "{Federal Univivesity of Mato Grosso do Sul (campus Campo Grande)} 
                         and {Federal Univivesity of Mato Grosso do Sul (campus Ponta 
                         Por{\~a})} and {Federal Univivesity of Mato Grosso do Sul (campus 
                         Campo Grande)} and {Anhaguera University - Uniderp} and {Federal 
                         Institute of Parana - IFPR} and {Dom Bosco Catholic University - 
                         UCDB}",
                title = "Using Color for Fish Species Classification",
            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 = "Fish Species Classification, Bag of Visual Words, Color images, 
                         Computer Vision.",
             abstract = "This paper presents an application dedicated to mobile devices 
                         whose objective is to classify fish species, using images and 
                         concepts of Computer Vision and Artificial Intelligence. The 
                         application was developed to Android smartphones with the help of 
                         OpenCV Computer Vision library for classification and training 
                         phases. The techniques employed in the description of the images 
                         are based on Bag of Visual Words applied to color images. They 
                         are: HSV and RGB color histograms, Bag of Visual Words, Bag of 
                         Features and Colors, Bag of Colors and Bag of Colored Words 
                         (BoCW). For the species classification, three types of classifiers 
                         was used: Support Vector Machine (SVM), Decision Tree and 
                         K-Nearest Neighbors algorithm (KNN). In the experiments several 
                         parameters for all the classifiers were tested in order to find 
                         the best results for classification. To compare the performance of 
                         the feature extraction techniques, as well as the classifiers, the 
                         metrics F-Score were used as the main metric and the Area Under 
                         the Curve (AUC) as an auxiliary metric. The technique with best 
                         result was BoC using the SVM classifier.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
             language = "en",
                  ibi = "8JMKD3MGPAW/3MCCQ48",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3MCCQ48",
           targetfile = "Paper.pdf",
        urlaccessdate = "2024, May 01"
}