Study on Image Recognition in Tank/Hold of Ship

Abstract

There is a movement to try to utilize the drone for checking inside the tank / hold of the ship. Access to the inspection site becomes easy, while on the other hand, since the site is judged through images taken by a drone, a technique for supporting state evaluation on the screen is desired. In this research, we applied the detection technology using deep learning (Faster R - CNN) to the recognition of structural members in hold of bulk carrier as the first stage. Because we have few experience of flying drone in tank / hold, here we learned and recognized based on the images taken at inspection. In addition to recognition in a bright environment, we also conducted virtual experiments simulating the dark environment inside the tank, verified and interpreted the recognition rate, and arranged issues for practical application.