Image technology based detection of infected shrimp in adverse environments
In recent years, countries around Japan and especially in Southeast Asia, white spot disease (WSD) is highly infectious and severely damages shrimp aquaculture. At the same time, the various diseases are occurring in shrimp farms. In the early stages of infection, shrimp shows three abnormal behav...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Prince of Songkla University
2022-02-01
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| Series: | Songklanakarin Journal of Science and Technology (SJST) |
| Subjects: | |
| Online Access: | https://rdo.psu.ac.th/sjst/journal/44-1/17.pdf |
| _version_ | 1818209102622359552 |
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| author | Thi Thi Zin Takehiro Morimoto Naraid Suanyuk Toshiaki Itami Chutima Tantikitti |
| author_facet | Thi Thi Zin Takehiro Morimoto Naraid Suanyuk Toshiaki Itami Chutima Tantikitti |
| author_sort | Thi Thi Zin |
| collection | DOAJ |
| description | In recent years, countries around Japan and especially in Southeast Asia, white spot disease (WSD) is highly infectious
and severely damages shrimp aquaculture. At the same time, the various diseases are occurring in shrimp farms. In the early
stages of infection, shrimp shows three abnormal behaviors: (1) they appear in the shallow waters of the farm, (2) they do not
move and do not eat even when feeding, and (3) they suddenly stop moving. Currently, infected shrimps are found by visual
inspection, which places a burden on the farmers and delays the discovery. Therefore, in this paper, we proposed a system for
detecting infected shrimp by using image processing technology in order to eliminate the delay of discovery and reduce the
burden of farmers. According to our experimental results, the proposed system has 95% precision, 100% recall rate and an
accuracy of 96.4% by using hold-out evaluation method. |
| first_indexed | 2024-12-12T04:55:23Z |
| format | Article |
| id | doaj.art-69e782acbfc743df9e639e939b3aaf30 |
| institution | Directory Open Access Journal |
| issn | 0125-3395 |
| language | English |
| last_indexed | 2024-12-12T04:55:23Z |
| publishDate | 2022-02-01 |
| publisher | Prince of Songkla University |
| record_format | Article |
| series | Songklanakarin Journal of Science and Technology (SJST) |
| spelling | doaj.art-69e782acbfc743df9e639e939b3aaf302022-12-22T00:37:21ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952022-02-0144111211810.14456/sjst-psu.2022.17Image technology based detection of infected shrimp in adverse environmentsThi Thi Zin0Takehiro Morimoto1Naraid Suanyuk2Toshiaki Itami3Chutima Tantikitti4Department of Electrical and Systems Engineering, Faculty of Engineering, University of Miyazaki, Miyazaki, 8892192 JapanDepartment of Electrical and Systems Engineering, Faculty of Engineering, University of Miyazaki, Miyazaki, 8892192 JapanAquatic Science and Innovative Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai, Songkhla, 90110 ThailandDepartment of Marine Bio-Science, Faculty of Life Science and Biotechnology, Fukuyama University, Fukuyama, Hiroshima, 7290292 JapanAquatic Science and Innovative Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai, Songkhla, 90110 ThailandIn recent years, countries around Japan and especially in Southeast Asia, white spot disease (WSD) is highly infectious and severely damages shrimp aquaculture. At the same time, the various diseases are occurring in shrimp farms. In the early stages of infection, shrimp shows three abnormal behaviors: (1) they appear in the shallow waters of the farm, (2) they do not move and do not eat even when feeding, and (3) they suddenly stop moving. Currently, infected shrimps are found by visual inspection, which places a burden on the farmers and delays the discovery. Therefore, in this paper, we proposed a system for detecting infected shrimp by using image processing technology in order to eliminate the delay of discovery and reduce the burden of farmers. According to our experimental results, the proposed system has 95% precision, 100% recall rate and an accuracy of 96.4% by using hold-out evaluation method.https://rdo.psu.ac.th/sjst/journal/44-1/17.pdfinfected shrimp detectionimage processing techniquesshrimp feeding behaviorsartificial sea water |
| spellingShingle | Thi Thi Zin Takehiro Morimoto Naraid Suanyuk Toshiaki Itami Chutima Tantikitti Image technology based detection of infected shrimp in adverse environments Songklanakarin Journal of Science and Technology (SJST) infected shrimp detection image processing techniques shrimp feeding behaviors artificial sea water |
| title | Image technology based detection of infected shrimp in adverse environments |
| title_full | Image technology based detection of infected shrimp in adverse environments |
| title_fullStr | Image technology based detection of infected shrimp in adverse environments |
| title_full_unstemmed | Image technology based detection of infected shrimp in adverse environments |
| title_short | Image technology based detection of infected shrimp in adverse environments |
| title_sort | image technology based detection of infected shrimp in adverse environments |
| topic | infected shrimp detection image processing techniques shrimp feeding behaviors artificial sea water |
| url | https://rdo.psu.ac.th/sjst/journal/44-1/17.pdf |
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