A survey on fish classification techniques
Fish classification (FC) is an expansively studied problem in the domains of image segmentation, pattern recognition, and information retrieval. It has been applied in a countless number of domains including target marketing. Meanwhile, governments are obliged to maintain the fish supply and balance...
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| Format: | Article |
| Language: | English |
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Springer
2022-05-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157820304195 |
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| author | Mutasem K. Alsmadi Ibrahim Almarashdeh |
| author_facet | Mutasem K. Alsmadi Ibrahim Almarashdeh |
| author_sort | Mutasem K. Alsmadi |
| collection | DOAJ |
| description | Fish classification (FC) is an expansively studied problem in the domains of image segmentation, pattern recognition, and information retrieval. It has been applied in a countless number of domains including target marketing. Meanwhile, governments are obliged to maintain the fish supply and balance between the ecosystem, commercial, agriculture field, marine scientists, and industrial arena of fish including the nutrition and canning factories. The various FC techniques performance is compared relying on the availability of preprocessing and feature extraction methods, the number of extracted features and classification accuracy, the number of fish families/species recognized. This survey also reviewed the use of Databases such as Fish4-Knowledge (F4K), knowledge database, and Global Information System (GIS) on Fishes and other FC databases. The study on preprocessing methods features extraction techniques and classifiers are gathered from recent works to enhance the understanding of the characteristics of preprocessing methods, features extraction techniques, and classifiers to guide future research directions and compensate for current research gaps. |
| format | Article |
| id | doaj-art-8f1c0450df7b47b78467da8074e95b43 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-8f1c0450df7b47b78467da8074e95b432025-08-20T03:51:58ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-05-013451625163810.1016/j.jksuci.2020.07.005A survey on fish classification techniquesMutasem K. Alsmadi0Ibrahim Almarashdeh1Corresponding author.; Department of MIS, College of Applied Studies and Community Service, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaDepartment of MIS, College of Applied Studies and Community Service, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaFish classification (FC) is an expansively studied problem in the domains of image segmentation, pattern recognition, and information retrieval. It has been applied in a countless number of domains including target marketing. Meanwhile, governments are obliged to maintain the fish supply and balance between the ecosystem, commercial, agriculture field, marine scientists, and industrial arena of fish including the nutrition and canning factories. The various FC techniques performance is compared relying on the availability of preprocessing and feature extraction methods, the number of extracted features and classification accuracy, the number of fish families/species recognized. This survey also reviewed the use of Databases such as Fish4-Knowledge (F4K), knowledge database, and Global Information System (GIS) on Fishes and other FC databases. The study on preprocessing methods features extraction techniques and classifiers are gathered from recent works to enhance the understanding of the characteristics of preprocessing methods, features extraction techniques, and classifiers to guide future research directions and compensate for current research gaps.http://www.sciencedirect.com/science/article/pii/S1319157820304195Features extractionShape featuresTexture featuresColor featuresImage segmentationFish classification algorithms |
| spellingShingle | Mutasem K. Alsmadi Ibrahim Almarashdeh A survey on fish classification techniques Journal of King Saud University: Computer and Information Sciences Features extraction Shape features Texture features Color features Image segmentation Fish classification algorithms |
| title | A survey on fish classification techniques |
| title_full | A survey on fish classification techniques |
| title_fullStr | A survey on fish classification techniques |
| title_full_unstemmed | A survey on fish classification techniques |
| title_short | A survey on fish classification techniques |
| title_sort | survey on fish classification techniques |
| topic | Features extraction Shape features Texture features Color features Image segmentation Fish classification algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S1319157820304195 |
| work_keys_str_mv | AT mutasemkalsmadi asurveyonfishclassificationtechniques AT ibrahimalmarashdeh asurveyonfishclassificationtechniques AT mutasemkalsmadi surveyonfishclassificationtechniques AT ibrahimalmarashdeh surveyonfishclassificationtechniques |