Mussel Classifier System Based on Morphological Characteristics

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...

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Bibliographic Details
Published in:IEEE access 2018, Vol.6, p.76935-76941
Main Authors: Coelho-Caro, Pablo A., Saavedra-Rubilar, Carlos E., Staforelli, Juan P., Gallardo-Nelson, MARIA J., Guaquin, Victor, Tarifeno, Eduardo
Format: Article
Language:English
Subjects:
Cameras
Classifiers
Digital imaging processing
Feature extraction
Human resources
Lighting
machine learning
Machine vision
Mollusks
Morphology
mussel classification
Mussels
real-time classification
Recognition
Sorting
Valves
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Summary: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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2884394