Method of Estimating River Levels with Reflective Tapes Using Artificial Vision Techniques

Abstract

Water level measurement in a river is a necessary step for flood prevention. Early recognition of this factor could reduce the vulnerability of the population in the surroundings. In this work, we use frames from videos as images to obtain water level measurement indirectly. We applied digital image processing techniques over these images to perform segmentation, edge detection, and we also applied multiple view geometry techniques as projective transformation in a plane. The proposed method estimates water level in specific locations where it is possible to install a reflective tape with a two-color pattern, used as an indicator of water level. We obtained the segmentation of the section out of the water of the reflective tape and so we get the estimation of water level. Through the relation of the real distances (in centimeters) that have four collinear points, seen from a perpendicular view, with the distances (in pixel unit) of those same points contained in an image, which has undergone a projective transformation. We made testing in a water tank built to this work and the tests produced a percentage error at the range of 0.01–2.06% to a distance of 1.5 m from a wall and 2 m high (location of camera).