Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues
| dc.contributor.author | Mohammadmehdi Saberioon | |
| dc.contributor.author | Asa Gholizadeh | |
| dc.contributor.author | Petr Cisar | |
| dc.contributor.author | Aliaksandr Pautsina | |
| dc.contributor.author | Jan Urban | |
| dc.date.accessioned | 2025-04-07T15:26:45Z | |
| dc.date.available | 2025-04-07T15:26:45Z | |
| dc.date.issued | 2015-12 | |
| dc.description.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. | en_US |
| dc.identifier.uri | https://umt-ir.umt.edu.my/handle/123456789/21651 | |
| dc.language.iso | en | en_US |
| dc.publisher | Wiley Publishing Asia Pty Ltd | en_US |
| dc.subject | aquaculture | en_US |
| dc.subject | accuracy and uncertainty | en_US |
| dc.subject | aquaculture management | en_US |
| dc.subject | fish quality | en_US |
| dc.subject | machine vision systems | en_US |
| dc.subject | optical sensors | en_US |
| dc.title | Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues | en_US |
| dc.type | Article | en_US |