Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images

Co-AuthorJournal Article
Amjad Khan, Syed Saad Azhar Ali, Atif Anwer, Syed Hasan Adil, Fabrice Mériaudeau
IEEE Access, vol. 6, pp. 40585-40601, 2018.
Publication year: 2018

Subsea pipeline corrosion is considered as a severe problem in offshore oil and gas industry. It directly affects the integrity of the pipeline which further leads to cracks and leakages. At present, subsea visual inspection and monitoring is performed by trained human divers; however, offshore infrastructures are moving from shallow to deep waters due to exhaustion of fossil fuels. Therefore, inhospitable underwater environmental conditions for human diver demand imaging-based robotic solution as an alternate for visual inspection and monitoring of subsea pipelines. However, an unfriendly medium is a challenge for underwater imaging-based inspection and monitoring activities due to absorption and scattering of light that further leads to blur, color attenuation, and low contrast. This paper presents a new method for subsea pipeline corrosion estimation by using color information of corroded pipe.

Underwater 3D Scene Reconstruction Using new Kinect sensor Based on Physical Models for Refraction and Time of Flight Correction

Journal Article
A. Anwer, S. S. A. Ali, Amjad Khan, F. Mériaudeau
IEEE Access, 2017 - (Q1, IF: 3.557)
Publication year: 2017

Commercial depth cameras have recently been tested to work underwater with trade off in measured depth distance but providing several advantages over conventional depth acquisition sensors such as Sonars and LiDARS. The biggest advantage is real-time 3D reconstruction and significantly better accuracy for small scale 3D scanning of submerged objects. Since traditional issues that are faced while using normal imaging cameras such as dependence on light and turbidity of water etc. are avoided, commercial depth cameras can open a new direction in small scale 3D scene reconstruction. This paper is an extension of our previous work in which we provided proof of concept that the Microsoft Kinect v2, which is a time of flight depth sensor, provides real-time 3D scanning in underwater environment, albeit at a shorter distance. However, the working of the time of flight sensor showed several issues in depth measurement in underwater environment. Preliminary results after correction of the measured distance are also provided in this work. Furthermore, the RGB and NIR cameras of Kinect v2 are not designed to perform underwater. To cater for the unwanted effects in the depth values, camera calibration has been performed on underwater images acquired from Kinect v2 and the results are elaborated. A fast, accurate and intuitive refraction correction method has been developed providing real-time correction to the created 3D mesh.

DOI: 10.1109/ACCESS.2017.2733003