• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.88-96
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• 2021

In surface image velocimetry, a wide area of a river is photographed at an angle to measure its velocity, inevitably causing image distortion. Although a distorted image can be corrected into an orthogonal image by using 2D projective coordinate transformation and considering reference points on the same plane as the water surface, this method is limited by the uncertainty of changes in the water level in the event of a flood. Therefore, in this study, we developed a tilt image correction technique that corrects distortions in oblique images without resetting the reference points while coping with changes in the water level using the geometric relationship between the coordinates of the reference points set at a high position the camera, and the vertical distance between the water surface and the camera. Furthermore, we developed a distortion correction method to verify the corrected image, wherein we conducted a full-scale river experiment to verify the reference point transformation equation and measure the surface velocity. Based on the verification results, the proposed tilt image correction method was found to be over 97% accurate, whereas the experiment result of the surface velocity differed by approximately 4% as compared to the results calculated using the proposed method, thereby indicating high accuracy. Application of the proposed method to an image-based fixed automatic discharge measurement system can improve the accuracy of discharge measurement in the event of a flood when the water level changes rapidly.