Open AccessMussel Classifier System Based on Morphological Characteristics
Author(s) -
Pablo A. Coelho-Caro,
Carlos E. Saavedra-Rubilar,
Juan P. Staforelli,
MARIA J. Gallardo-Nelson,
Victor Guaquin,
Eduardo Tarifeno
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2884394
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The recognition, counting, and sorting of mussels in marine cultures for seed production are currently performed by visual examination experts (i.e., entirely dependent on human resources). In this paper, we present the development of an automatic mussel classifier system based on the morphological characteristics for the simultaneous recognition and sorting of five mussel species. The proposed system provides rich statistical information needed for tracking the long-term evolution of culture parameters. In our experimental demonstration, we have achieved a recognition rate of 95% in most of the test probes for the five studied mussel species. A single sample of dozens of specimens can be classified within seconds with real-time capability when the vision interface is not used. Finally, the system has the potential to be extended for the automatic classification of mussels worldwide.
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