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The Identification of hunger behaviour of lates calcarifer through the integration of image processing technique and support vector machine

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.

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Abstract

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.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 6616/65312
Uncontrolled Keywords: Identification of hunger; Behaviour of lates calcarifer; Integration of image processing; Technique and support vector machine
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Science
Depositing User: Dr. Yukinori Mukai
Date Deposited: 01 Aug 2018 14:15
Last Modified: 24 Jan 2019 14:46
URI: http://irep.iium.edu.my/id/eprint/65312

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