Robust Image-Based Water-Level Estimation Using Single-Camera Monitoring

This study proposes an automatic image water-level measurement system using a single camera. The inverse perspective mapping (IPM) technology is used to rectify an image to improve deviations because the optical axis of the camera and staff gauge are not orthogonal, causing a perspective distortion in the real environment. The initial position of the current watermark is first determined from the staff gauge's image by applying basic digital image-processing technology. The system uses the image histogram of staff gauge's region of interest to provide a reference region for determining accurate water levels from the preliminary watermark position. Furthermore, the proposed system can correctly and automatically determine the current water-level elevation by establishing the control points to convert the pixel distance to the real-world distance as well as through the setting of the reference water-level elevation. The images are shifted because of camera vibration, which will also shift the waterline coordinates. To prevent the image shift due to camera vibration from interfering with the accuracy of water-level measurement, we used the normalized cross correlation (NCC) technology with the proposed camera-vibration calibration scheme for removing the impact. The proposed distance calibration (DISCAL) module further optimizes the results of the images rectified using the IPM technology. The suggested automatic water-level measurement system can improve the traditional linear interpolation approach by >90%, and the deviation value of the real water level is < 0.5 cm, which is ideal for water-level measurement in confined spaces according to experimental results.