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  • Fish Counting and Measurement: A Modular Framework and Implementation

    Author(s)
    Westling, Fredrick Andrers
    Sun, Changming
    Wang, Dadong
    Alam, Fahim
    Griffith University Author(s)
    Alam, Fahim
    Year published
    2016
    Metadata
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    Abstract
    An approach is suggested for automating fish identification and measurement using stereo Baited Remote Underwater Video footage. Simple methods for identifying fish are not sufficient for measurement, since the snout and tail points must be found, and the stereo data should be incorporated to find a true measurement. We present a modular framework that ties together various approaches in order to develop a generalized system for automated fish detection and measurement. A method is also suggested for using machine learning to improve identification. Experimental results indicate the suitability of our approach.An approach is suggested for automating fish identification and measurement using stereo Baited Remote Underwater Video footage. Simple methods for identifying fish are not sufficient for measurement, since the snout and tail points must be found, and the stereo data should be incorporated to find a true measurement. We present a modular framework that ties together various approaches in order to develop a generalized system for automated fish detection and measurement. A method is also suggested for using machine learning to improve identification. Experimental results indicate the suitability of our approach.
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    Book Title
    Computer Vision and Pattern Recognition in Environmental Informatics
    DOI
    https://doi.org/10.4018/978-1-4666-9435-4.ch003
    Subject
    Pattern Recognition and Data Mining
    Publication URI
    http://hdl.handle.net/10072/141822
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    • Book chapters

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