The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine
Fish Hunger behaviour is one of the important element in determining the fish feeding routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding) lead the fishes to die and thus, reduces the total production of fishes. The excessive food which is not eaten b...
| Main Authors: | , , , , , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
Institute of Physics Publishing
2018
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/65312/ http://irep.iium.edu.my/65312/1/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_conference%20article.pdf http://irep.iium.edu.my/65312/2/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_scopus.pdf |
| _version_ | 1848786370184609792 |
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| author | Taha, Zahari Mohd Razman, Mohd Azraai A. Adnan, Fatihah Abdul Ghani, Ahmad Shahrizan P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Sallehudin, Muhammad Firdaus Mukai, Yukinori |
| author_facet | Taha, Zahari Mohd Razman, Mohd Azraai A. Adnan, Fatihah Abdul Ghani, Ahmad Shahrizan P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Sallehudin, Muhammad Firdaus Mukai, Yukinori |
| author_sort | Taha, Zahari |
| building | IIUM Repository |
| collection | Online Access |
| description | Fish Hunger behaviour is one of the important element in determining the fish feeding
routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding)
lead the fishes to die and thus, reduces the total production of fishes. The excessive food which
is not eaten by fish will be dissolved in the water and thus, reduce the water quality (oxygen
quantity in the water will be reduced). The reduction of oxygen (water quality) leads the fish to
die and in some cases, may lead to fish diseases. This study correlates Barramundi fish-school
behaviour with hunger condition through the hybrid data integration of image processing
technique. The behaviour is clustered with respect to the position of the centre of gravity of the
school of fish prior feeding, during feeding and after feeding. The clustered fish behaviour is
then classified by means of a machine learning technique namely Support vector machine
(SVM). It has been shown from the study that the Fine Gaussian variation of SVM is able to
provide a reasonably accurate classification of fish feeding behaviour with a classification
accuracy of 79.7%. The proposed integration technique may increase the usefulness of the
captured data and thus better differentiates the various behaviour of farmed fishes. |
| first_indexed | 2025-11-14T17:07:57Z |
| format | Proceeding Paper |
| id | iium-65312 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:07:57Z |
| publishDate | 2018 |
| publisher | Institute of Physics Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-653122019-11-29T05:05:03Z http://irep.iium.edu.my/65312/ The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine Taha, Zahari Mohd Razman, Mohd Azraai A. Adnan, Fatihah Abdul Ghani, Ahmad Shahrizan P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Sallehudin, Muhammad Firdaus Mukai, Yukinori Q Science (General) QA76 Computer software Fish Hunger behaviour is one of the important element in determining the fish feeding routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding) lead the fishes to die and thus, reduces the total production of fishes. The excessive food which is not eaten by fish will be dissolved in the water and thus, reduce the water quality (oxygen quantity in the water will be reduced). The reduction of oxygen (water quality) leads the fish to die and in some cases, may lead to fish diseases. This study correlates Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique. The behaviour is clustered with respect to the position of the centre of gravity of the school of fish prior feeding, during feeding and after feeding. The clustered fish behaviour is then classified by means of a machine learning technique namely Support vector machine (SVM). It has been shown from the study that the Fine Gaussian variation of SVM is able to provide a reasonably accurate classification of fish feeding behaviour with a classification accuracy of 79.7%. The proposed integration technique may increase the usefulness of the captured data and thus better differentiates the various behaviour of farmed fishes. Institute of Physics Publishing 2018-03-21 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/65312/1/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_conference%20article.pdf application/pdf en http://irep.iium.edu.my/65312/2/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_scopus.pdf Taha, Zahari and Mohd Razman, Mohd Azraai and A. Adnan, Fatihah and Abdul Ghani, Ahmad Shahrizan and P.P. Abdul Majeed, Anwar and Musa, Rabiu Muazu and Sallehudin, Muhammad Firdaus and Mukai, Yukinori (2018) The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine. In: 4th Asia Pacific Conference on Manufacturing Systems and the 3rd International Manufacturing Engineering Conference, APCOMS-iMEC 2017, 7-8 December 2017, Yogyakarta; Indonesia. http://iopscience.iop.org/article/10.1088/1757-899X/319/1/012028/pdf 10.1088/1757-899X/319/1/012028 |
| spellingShingle | Q Science (General) QA76 Computer software Taha, Zahari Mohd Razman, Mohd Azraai A. Adnan, Fatihah Abdul Ghani, Ahmad Shahrizan P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Sallehudin, Muhammad Firdaus Mukai, Yukinori The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title | The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title_full | The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title_fullStr | The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title_full_unstemmed | The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title_short | The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| title_sort | identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine |
| topic | Q Science (General) QA76 Computer software |
| url | http://irep.iium.edu.my/65312/ http://irep.iium.edu.my/65312/ http://irep.iium.edu.my/65312/ http://irep.iium.edu.my/65312/1/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_conference%20article.pdf http://irep.iium.edu.my/65312/2/65312_The%20Identification%20of%20Hunger%20Behaviour%20of%20Lates_scopus.pdf |