Overview of machine vision on digital imaging approach for automatic tuna length measurement

• Main Authors: Sukiman, A. R., Hassan, H., Mohd. Zain, A., Mukhtar, A., Panatik, K. Z.
• Format: Conference or Workshop Item
• Language: English
• Published: 2019
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/89611/1/AdamRidhwanSukiman2019_OverviewofMachineVisiononDigitalImaging.pdf; http://eprints.utm.my/id/eprint/89611/; http://www.dx.doi.org/10.1088/1757-899X/551/1/012076

The demand of fish and marine product have increased significantly throughout the year. Therefore, overfishing had become major concern for various parties around the world especially the United Nation(UN). Collecting numerical data is a first step toward preservation and conservation of tuna and other fish population. This paper reviews automatic tuna length measurement by using machine vision techniques. This is one of the steps in collecting necessary data on size of fishes caught by fishermen. Previous research had been done on measuring the length of fish, but the accuracy rate of the length measurement is not satisfactory enough. Many factors affecting the accuracy of the length measurement processes such as lighting inequalities, blood on the platform and others. Machine vision techniques have a great potential to be used in automating the measurement of the fish length with high accuracy. Machine vision techniques could improve the accuracy and efficiency of the measurement of the fish length that would substitute the tedious manual work.