Water Color Identification System for Monitoring Aquaculture Farms

Hsiang Chieh Chen, Sheng Yao Xu, Kai Han Deng

研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)


This study presents a vision-based water color identification system designed for monitoring aquaculture ponds. The algorithm proposed in this system can identify water color, which is an important factor in aquaculture farming management. To address the effect of outdoor lighting conditions on the proposed system, a color correction method using a color checkerboard was introduced. Several candidates for water-only image patches were extracted by performing image segmentation and fuzzy inferencing. Finally, a deep learning-based model was employed to identify the color of these patches and then find the representative color of the water. Experiments at different aquaculture sites verified the effectiveness of the proposed system and its algorithm. The color identification accuracy exceeded 96% for the test data.

期刊Sensors (Switzerland)
出版狀態已出版 - 10月 2022


深入研究「Water Color Identification System for Monitoring Aquaculture Farms」主題。共同形成了獨特的指紋。