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Identification of Birds Using Spectrogram Image Processing and Artificial Neural Network Classifiers

Identification of Birds Using Spectrogram Image Processing and Artificial Neural Network Classifiers AbstractIdentifying birds in audio signals has been a challenge because the marking of certain species influences their classification. The proposed method consists of a mixture of sound processing for extracting useful signals from longer recordings with dynamic energy thresholds, image processing such as filtering and compression through image resizing for the treatment of the spectrogram and multilayer perceptron networks for the classification. The method shows encouraging results and flexibility, allowing the extension to a larger number of species, as well as applications to other fields involving sound or sound-like signals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACTA Universitatis Cibiniensis de Gruyter

Identification of Birds Using Spectrogram Image Processing and Artificial Neural Network Classifiers

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Publisher
de Gruyter
Copyright
© 2020 Andrei-Ionuț Cheroiu et al., published by Sciendo
eISSN
1583-7149
DOI
10.2478/aucts-2020-0002
Publisher site
See Article on Publisher Site

Abstract

AbstractIdentifying birds in audio signals has been a challenge because the marking of certain species influences their classification. The proposed method consists of a mixture of sound processing for extracting useful signals from longer recordings with dynamic energy thresholds, image processing such as filtering and compression through image resizing for the treatment of the spectrogram and multilayer perceptron networks for the classification. The method shows encouraging results and flexibility, allowing the extension to a larger number of species, as well as applications to other fields involving sound or sound-like signals.

Journal

ACTA Universitatis Cibiniensis – de Gruyter

Published: Dec 1, 2020

Keywords: Identification of Birds; Spectrogram; ANN; Image Processing; Sound Processing

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