Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Active contour-based detection of estuarine dolphin whistles in spectrogram images

Texto completo
Autor(es):
Serra, O. M. [1] ; Martins, F. P. R. [1] ; Padovese, L. R. [1]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Escola Politecn, Dept Mech Engn, Av Prof Mello Moraes 2231, BR-05508030 Sao Paulo - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: ECOLOGICAL INFORMATICS; v. 55, JAN 2020.
Citações Web of Science: 0
Resumo

An algorithm for detecting tonal vocalizations from estuarine dolphin (Sotalia guianensis) specimens without interference of a human operator was developed. The raw audio data collected from a passive monitoring sensor in the Cananeia underwater soundscape was converted to spectrogram images. Detection is a four-step method: first, ridge maps are obtained from the spectrogram images; second, a probabilistic Hough transform algorithm is applied to detect ridges similar to thick line segments, referred to as line-like, which are adjusted to the geometry of the whistles in the images via an active contour algorithm; third, feature vectors are built from the geometry of each detected whistle, with 9 descriptive features; and fourth, the detections are fed to a random forest classifier to parse out mistakes by the detection process. We developed a system for classifying the characteristic patterns detected as Sotalia guianensis whistles or random empty detections. We obtained accuracy of 0.977 and F1-score of 0.981. (AU)

Processo FAPESP: 14/50279-4 - Brasil Research Centre for Gas Innovation
Beneficiário:Julio Romano Meneghini
Linha de fomento: Auxílio à Pesquisa - Programa Centros de Pesquisa em Engenharia