Protocols for Image Processing based Underwater Inspection of Infrastructure Elements

Image processing can be an important tool for inspecting underwater infrastructure elements like bridge piers and pile wharves. Underwater inspection often relies on visual descriptions of divers who are not necessarily trained in specifics of structural degradation and the information may often be vague, prone to error or open to significant variation of interpretation. Underwater vehicles, on the other hand can be quite expensive to deal with for such inspections. Additionally, there is now significant encouragement globally towards the deployment of more offshore renewable wind turbines and wave devices and the requirement for underwater inspection can be expected to increase significantly in the coming years. While the merit of image processing based assessment of the condition of underwater structures is understood to a certain degree, there is no existing protocol on such image based methods. This paper discusses and describes an image processing protocol for underwater inspection of structures. A stereo imaging image processing method is considered in this regard and protocols are suggested for image storage, imaging, diving, and inspection. A combined underwater imaging protocol is finally presented which can be used for a variety of situations within a range of image scenes and environmental conditions affecting the imaging conditions. An example of detecting marine growth is presented of a structure in Cork Harbour, Ireland.

[1]  R Frankbusby Underwater inspection/testing/ monitoring of offshore structures , 1979 .

[2]  R. Frank Busby Underwater inspection, testing, monitoring of offshore structures , 1979 .

[3]  Gerald J. Agin Computer Vision Systems for Industrial Inspection and Assembly , 1980, Computer.

[4]  Larry H. Matthies,et al.  Error modeling in stereo navigation , 1986, IEEE J. Robotics Autom..

[5]  O. D. Faugeras,et al.  Camera Self-Calibration: Theory and Experiments , 1992, ECCV.

[6]  Richard D. Zakia,et al.  The Focal encyclopedia of photography , 1993 .

[7]  Anup Basu,et al.  Analysis of Error in Depth Perception with Vergence and Spatially Varying Sensing , 1996, Comput. Vis. Image Underst..

[8]  L. Goldberg Diversity in underwater inspection , 1996 .

[9]  Benjamin A. Graybeal,et al.  Routine Highway Bridge Inspection Condition Documentation Accuracy and Reliability , 2004 .

[10]  Paul Fieguth,et al.  Automated detection of cracks in buried concrete pipe images , 2006 .

[11]  Luc Taerwe,et al.  fib Bulletin 42. Constitutive modelling of high strength / high performance concrete , 2008 .

[12]  Luc Taerwe,et al.  Constitutive modelling of high strength/high performance concrete: state-of-art report , 2008 .

[13]  Anders Olofsson,et al.  Modern Stereo Correspondence Algorithms : Investigation and Evaluation , 2010 .

[14]  Mohamed A. El-Reedy,et al.  Offshore Structures: Design, Construction and Maintenance , 2012 .

[15]  Djamel Merad,et al.  Underwater image preprocessing for automated photogrammetry in high turbidity water: An application on the Arles-Rhone XIII roman wreck in the Rhodano river, France , 2012, 2012 18th International Conference on Virtual Systems and Multimedia.

[16]  Vikram Pakrashi,et al.  Regionally Enhanced Multiphase Segmentation Technique for Damaged Surfaces , 2014, Comput. Aided Civ. Infrastructure Eng..

[17]  Mohamed A. El-Reedy 4 – Offshore structures design , 2015 .