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    A general purpose automatic detector of broadband transient signals in underwater audio

    Access Status
    Fulltext not available
    Authors
    Madhusudhana, S.
    Gavrilov, Alexander
    Erbe, Christine
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Madhusudhana, S. and Gavrilov, A. and Erbe, C. 2018. A general purpose automatic detector of broadband transient signals in underwater audio.
    Source Title
    2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
    DOI
    10.1109/OCEANSKOBE.2018.8559259
    ISBN
    9781538616543
    School
    Centre for Marine Science and Technology
    URI
    http://hdl.handle.net/20.500.11937/73899
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 IEEE. A spectrogram-based technique is presented for detection of time-and-bandwidth limited broadband signals in underwater audio. The approach employs an iterative 1-dimensional variant of a 2-dimensional multi-scale blob-detection technique commonly used in image processing. In contrast to the referenced 2-dimensional technique subject to an inherent bias for circular features, the iterative 1-dimensional approach enables detection of features of arbitrary bandwidth and duration. The iterative nature (of processing successive frames) makes it an attractive choice for in-situ streaming-mode applications. The algorithm automatically chooses values for several parameters based on the input spectrogram’s frequency bounds and hence is capable of being readily employed for a variety of applications. The technique’s applications include detection of broadband signals of interest, such as Omura’s whale (Balaenoptera omurai) calls, underwater earthquakes or explosions. With long-term spectral averages, the technique may be used in identifying long-lasting sounds contributing to ambient noise, such as fish choruses or the sounds of wind and rain. A theoretical analysis of the proposed technique’s performance is provided and its detection capability is demonstrated using representative examples.

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