Bird species classification using spectrograms

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%.