Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues
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Date
2015-12
Journal Title
Journal ISSN
Volume Title
Publisher
Wiley Publishing Asia Pty Ltd
Abstract
Demands of aquatic products are increasing dramatically during past decades.
Also quality assurance has gradually received more attention by both producers
and consumers. Thus, fish producers are exploring all possible approaches for
improving the productivity and profitability. Monitoring of fish state and behaviour
during cultivation may help to improve profitability for producers and also
reduce the threat of severe loss because of disease and stress incidents. It is necessary
to evaluate and measure quality of fish products in accurate, fast and objective
way for meeting the different demands of the fish-processing industry after
harvesting. Traditional methods are usually time-consuming, expensive, laborious
and invasive. Using rapid, inexpensive and noninvasive methods is therefore
important and desirable. Optical sensors and machine vision system provide the
possibility of developing faster, cheaper and noninvasive methods for in situ and
after harvesting monitoring of quality in aquaculture. This review describes the
most recent technologies and the suitability of different optical sensors for the fish
farming management and also assessment, measurement and prediction of fish
products quality. Two major areas of optical sensors applications in aquaculture
are discussed in this review: (i) preharvesting and during cultivation; and (ii)
post-harvesting. Finally, accuracy and uncertainty of optical sensors applications
in aquaculture are discussed. This review showed that MVSs and optical sensors
have found real-world application based on tremendous possibility offered by
digital camera development and increasing the speed of computer-based processing;
however, still new algorithms, methods and re-engineered sensors need to be
developed to meet real-world requirements.
Description
Keywords
aquaculture, accuracy and uncertainty, aquaculture management, fish quality, machine vision systems, optical sensors