Study of Image-Based Automatic River Flow Velocity Measurement

• Main Authors: Sun, Yi-Chieh, 孫易頡
• Other Authors: Lin, Sheng-Fuu
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/k8rrtk

碩士 === 國立交通大學 === 電控工程研究所 === 104 === Nowadays, we are deeply impacted by global warming and extremely climate change. With the tendency to enhance disaster occurred, the number of relevant monitoring system is used along with the growth of the field of hydrological disaster prevention. However, there are several limitations in the system of conventional monitors, including need to check disaster events by people, the instrument damaged and security of surveying staff. In this thesis, we design an intelligent video surveillance to reduce the loading of human resource and improve the security of measurement. There are three contributions of this thesis. First, this thesis proposes a feature-based tracking of drifting objects algorithm, including Retinex enhancement and feature-based tracking to detect drifting objects accurately. Second, this thesis proposes data reconciliation mechanism to improve the accuracy of river flow velocity measurement. Finally, this thesis completes the prototype of system in automatic river flow velocity measurement to reduce the loading of employees and risk of measurement.