High Resolution Visual Pipe Characterization System Using an Omnidirectional Camera
Date
2015-07
Authors
Dehghan Tezerjani, Abbasali
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Graduate Studies and Research, University of Regina
Abstract
Machine vision techniques are applied in a wide variety of industries around the
world for quality inspection of the products. One area that is getting a signi cant
amount of attention is pipelines. Pipe manufacturers strive to do fast and reliable
quality control. Furthermore, pipeline users are justly concerned about the sustainability
of their aging infrastructure. Timely pro-active inspection is, therefore,
paramount in balancing maintenance cost over time.
Omnidirectional imaging systems are gaining world-wide attention due to their
cost e ectiveness, fast calibration, and size factor. However, due to their high distortion,
they are rarely used for pipe inspection applications. This research attempts
to provide a comprehensive and cost-e ective solution for the characterization of the
inner surface of a pipe using omnidirectional sensors. This solution includes detection,
classi cation, and position-referencing of the visual surface defects, and nally
reconstructing of the interior surface of the pipe in 3D.
First, a comprehensive study on the optimal spatial resolution of omnidirectional sensors for the pipe inspection applications is presented. This provides a guideline
in selecting the omnidirectional sensor for achieving the highest resolution in the
system. A mobile platform is also designed for inspecting the interior surface of the
pipe using the selected omnidirectional sensor. To estimate the position of the sensor
inside the pipe, a novel algorithm based on nonlinear optimization was designed.
Furthermore, a new algorithm is presented for detecting and classifying the visible
defects. In addition, a novel texture representation algorithm is presented to overcome
the challenges of the visual odometry for the seamless textures ( e.g. PVC pipes).
Finally, a complete platform for reconstructing the interior surface of a pipe in 3D is
presented. The proposed platform for pipe characterization has been tested in a lab
con guration, and satisfactory results have been achieved.
Description
A Thesis Submitted to the Faculty of Graduate Studies and Research in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy in Industrial Systems Engineering, University of Regina. xvi, 201 p.