Fish Counting and Measurement: A Modular Framework and Implementation
Author(s)
Westling, Fredrick Andrers
Sun, Changming
Wang, Dadong
Alam, Fahim
Griffith University Author(s)
Year published
2016
Metadata
Show full item recordAbstract
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
Subject
Pattern Recognition and Data Mining