Intelligent Visual Inspection System of Ship Draft Based on UAV

Abstract

Accurately calculating the weight of cargo after shipping is an important issue in ocean transportation. Existing methods mainly indirectly calculate the weight of cargo by obtaining the draft of the ship. To estimate the draft of ships passing through waterways and ports, it is necessary to collect sounding line data. However, the current methods for collecting sounding line data mainly rely on manual measurement, which is inefficient, inaccurate, and has safety hazards. To address these issues, this paper combines artificial intelligence and deep learning technologies to design an unmanned aerial vehicle-based intelligent detection system for ship drafts. Detailed research is conducted on image acquisition, image segmentation, image recognition algorithms, etc., and an intelligent measurement platform for ship drafts is developed.