Bird Species Classification Using Spectrograms
Diego Rafael Lucio$^{1}$, Yandre Maldonado e Gomes da Costa$^{1}$
$^{1}$Universidade Estadual de Maringá. Paraná Brazil
Schedule:Tue 20th@11:45, Room: A

This paper describes a system for automatic bird species classification based on features taken from the textural content of spectrogram images. The texture features are extracted using three of the most common texture operators described in the Digital Image Processing literature: Local Binary Pattern (LBP), Local Phase Quantization (LPQ) and Gabor Filters. Aiming to perform more fare comparisons, the experiments were performed over a database already used in other works presented in the literature. In the classification step, SVM classifier was used and the final results were taken using 10-fold cross validation. The experiments were performed over a challenger dataset composed of 46 classes, and the best accuracy rate obtained is about 77.65%.


	author 		= {Diego Rafael Lucio and Yandre Maldonado e Gomes da Costa},
	title 		= {Bird Species Classification Using Spectrograms},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {335--345},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {},
	isbn 		= {978-1-4673-9143-6},

Generated by Ernesto Cuadros-Vargas , Sociedad Peruana de Computación-Peru, Universidad Católica San Pablo, Arequipa-Perú