A Novel Centralization Method for Pipe Image Stitching

The creation of unwrapped stitched images of pipework internal surfaces is being increasingly used to augment routine visual inspection. A significant challenge to the creation of these stitched images is the need to estimate the pose and position of the camera for each frame, which is often alleviated through the use of a mechanical centralizer to ensure the camera is held in the center of the pipe. This article proposes a novel method for image centralization and pose estimation, which is particularly beneficial to circumstances where mechanical centralization is impractical. The approach involves post-inspection centralization of the captured video, by first estimating the probe's position relative to the pipe, using an integrated laser ring projector combined with the camera sensor, and then using this position to unwrap the image, so it produces an undistorted view of the pipe interior (equivalent to unwrapping a centralized view). These unwrapped images are then stacked to produce a stitched image of the pipe interior. In this paper pose estimation was successfully demonstrated to have a 90% confidence interval of +/- 0.5 mm and +/- 0.5 degrees in translation and rotation changes. This pose estimation is then used to create stitched images for both a visual test card image mounted inside a pipe and an aluminum pipe sample with artificial defects, in both cases demonstrating near equivalent results to those obtained using traditional mechanical centralization.

Automated summary

The article proposes a novel method for creating unwrapped stitched images of pipework internal surfaces, involving estimation of the probe's position relative to the pipe using an integrated laser ring projector and camera sensor, followed by unwrapping the image to produce an undistorted view of the pipe interior. The pose estimation demonstrated a 90% confidence interval of +/- 0.5 mm and +/- 0.5 degrees in translation and rotation changes, and the method showed near equivalent results to traditional mechanical centralization in testing on visual test card images and aluminum pipe samples with artificial defects.