Water elevation measurements using binary image analysis for 2D hydrodynamic experiments

Green Water on A Fixed Structure Due to Incident Bores: Guidelines and Database for Model Validations Regarding Flow Evolution

“…Measurements of water elevation were obtained from several virtual wave probes (VWPs), from the video made by the cameras that were parallel to the side view of the tank, that is, CAM1 for EXP1 and EXP2, and CAM2 for EXP2. To obtain the water elevation measurements, the open-source image-based methodology developed by [29] was employed. The methodology includes the three main stages of an artificial vision system: Image acquisition, processing, and analysis.…”

“…Finally, through basic morphological operations, image analysis was carried out from the binary images to obtain water elevations at different regions of interest, which were recorded by the virtual wave probes (VWPs). See the work of [29] for more details regarding the procedures for image calibration, processing, and analysis to obtain the water elevation measurements.…”

“…Considering that the conventional wave probes can be subjected to different sources of error due to installation and performance (see, for instance, [1,29]), the applicability of the image-based approach was considered acceptable for the purposes of the present work.…”

A simplified and open-source approach for multiple-valued water surface measurements in 2D hydrodynamic experiments

“…Commonly, these sensors are made of thin rods or wires and operated under conductive, capacitive or resistive methods. However, this type of sensor may not be ideal in providing real-water elevation measurements, particularly when the flow, at a specified location, has several surfaces [20,21].…”

“…More recently, Hernández et al [21] proposed an alternative open-source image-based approach based on analyses of binary images to measure the effective water heights at desired positions over the fluid propagation domain. This type of binary-based methodologies present the advantage to be computationally efficient since the processing of binary images is faster than that employed for color or grayscale images [26].…”