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 Remotely Operated Vehicle (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. In this study, the development of a vision system guiding an Autonomous Underwater Vehicle (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 tracks the cable with an average success rate above 90%. 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.

[1]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[2]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[3]  M. D. Iwanowski.  Surveillance unmanned underwater vehicle , 1994, Proceedings of OCEANS'94.

[4]  Kenichi Asakawa,et al.  Cable tracking for autonomous underwater vehicle , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).

[5]  Primo Zingaretti,et al.  Imaging approach to real-time tracking of submarine pipeline , 1996, Electronic Imaging.

[6]  Hoa G. Nguyen,et al.  Machine Visual Guidance For An Autonomous Undersea Submersible , 1988, Optics & Photonics.

[7]  Gabriel Oliver,et al.  A vision system for underwater real-time control tasks , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[8]  G. Oliver,et al.  Optimized image sequence analysis for real-time underwater cable tracking , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[9]  Y. Ito,et al.  Real-time vision-based tracking of submarine-cables for AUV/ROV , 1995, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE.

[10]  Shahriar Negahdaripour,et al.  Vision-based motion sensing for underwater navigation and mosaicing of ocean floor images , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[11]  C. Aage,et al.  Pipeline inspection using an autonomous underwater vehicle , 1995 .

[12]  Tamaki Ura,et al.  Vision based autonomous underwater vehicle navigation: underwater cable tracking , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[13]  J. Santos-Victor,et al.  The role of vision for underwater vehicles , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).