A binocular vision-based underwater object size measurement paradigm: Calibration-Detection-Measurement (C-D-M)

Abstract

In this study, we propose a binocular vision-based underwater object size measurement paradigm: Calibration-Detection-Measurement (C-D-M). In the C-procedure, we construct an underwater refraction model to calculate basic parameters and refractive parameters of an underwater binocular vision system in waterproof housing. These parameters are key to realising the conversion of 2D pixel coordinates to 3D world coordinates. In the D-procedure, we attempt to address the difficult problem of underwater object detection via multi-feature joint perception, and accurately segment the regions of underwater objects in binocular images. Subsequently, the object regions and 3D reconstruction parameters are input into the M-procedure to measure the sizes of underwater objects. Specifically, a novel contour curve matching strategy is presented instead of dense matching to acquire reliable matching points. Subsequently, a 3D contour curve is reconstructed to calculate the key sizes of objects. Finally, comprehensive evaluations are conducted to demonstrate the effectiveness of our C-D-M paradigm.