Machine Vision-Based Automatic Raw Fish Handling and Weighing System of Taiwan Tilapia

Authors:
Yu-Teng Liang;Yih-Chih Chiou
Affiliations:
Institute of Engineering Science, Chung-Hua University, Hsinchu, Taiwan 300 and Department of Automation Engineering, Ta Hwa Institute of Technology, Hsinchu, Taiwan 30740;Institute of Engineering Science, Chung-Hua University, Hsinchu, Taiwan 300
Venue:
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Year:
2009

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Abstract

This study proposes a vision-based automatic raw fish handling system to speed up fish cleaning and weighing. The proposed fish weighing system used a camera to capture projected images of fishes. Applying image processing techniques, physical properties of fishes, such as length, width, perimeter and area were obtained. Followed by regression analysis, weight-length, weight-height, weight-perimeter and weight-area relationships were derived. Analysis results of fifty tilapias show that coefficient of determination of the regression equation relating weight and area is 0.9303. The high value suggests that a tilapia's weight is highly correlated with its projected area. Therefore, use a tilapia's area to estimate its weight is justifiable.