Water Speed Measurement Using Particle Tracking and OpenCV

This paper is part of a project sponsored by Central Water and Power Research Station, Khadkwasla, Pune (CWPRS). The project focuses on finding the speed of water flow using Computer Vision techniques with particle introduction in water. It is an excellent idea to use OpenCVto determine the speed of water since it is affordable, non-intrusive, more accurate, and adaptable in terms of the situations in which it may be utilized. When an object is suspended in water, the behavior of the object depends on the balance of forces acting on it, including surface tension, drag, buoyant force, and flow patterns. The mobility of objects in motion can be examined using various techniques, including Particle Image Velocimetry (PIV), Optical Flow, Kalman Filter, Mean Shift Algorithm, and more. The main motivation behind this study was to determine the flow rate and unique method for estimating the velocity of water. The goal was to evaluate the performance of the following four methods: PIV, Optical Flow, Kalman Filter, and Mean Shift Algorithm on stable background video and challenging turbulent water background video. Each technique's performance was compared, and its advantages and disadvantages were assessed.