Abstract
We use signal and image theory based algorithms to produce estimations of the number of wolves emitting howls or barks in a given field recording as an individuals counting alternative to the traditional trace collecting methodologies. We proceed in two steps. Firstly, we clean and enhance the signal by using PDE based image processing algorithms applied to the signal spectrogram. Secondly, assuming that the wolves chorus may be modelled as an addition of nonlinear chirps, we use the quadratic energy distribution corresponding to the Chirplet Transform of the signal to produce estimates of the corresponding instantaneous frequencies, chirp-rates and amplitudes at each instant of the recording. We finally establish suitable criteria to decide how such estimates are connected in time.
All authors are supported by Project PC07-12, Gobierno del Principado de Asturias, Spain. Third and fourth authors are supported by the Spanish DGI Project MTM2007-65088.
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Dugnol, B., Fernández, C., Galiano, G., Velasco, J. (2008). On a Chirplet Transform Based Method for Co-channel Voice Separation. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2008. Communications in Computer and Information Science, vol 25. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92219-3_12
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DOI: https://doi.org/10.1007/978-3-540-92219-3_12
Publisher Name: Springer, Berlin, Heidelberg
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