Optimized image sequence analysis for real-time underwater cable tracking

Nowadays, the surveillance and inspection of underwater installations, such as power and telecommunication cables and pipelines, is carried out by operators that, being on the surface, drive a ROV with cameras mounted over it. This is a tedious and high time-consuming task, easily prone to errors mainly because of loss of attention or fatigue of the human operator. Besides, the complexity of the task is increased by the lack of quality of typical seabed images, which are mainly characterised by blurring, nonuniform illumination, lack of contrast and instability in the vehicle motion. In this study, the development of a vision system guiding an AUV able to detect and track automatically an underwater power cable laid on the seabed has been the main concern. The vision system that is proposed is able to track the cable with an average success rate above 90% while maintaining real-time performance. The system has been tested using sequences coming from a video tape obtained in several tracking sessions of various real cables with a ROV driven from the surface. These cables were installed several years ago, so that the images do not present highly contrasted cables over a sandy seabed; on the contrary, these cables are partially covered in algae or sand, and are surrounded by other algae and rocks, making thus the sequences highly realistic.