Hyper resolution image mosaics with unbounded vertical field of view

König, Jakob; O’Leary, Paul

doi:10.1016/j.compind.2020.103281

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…The system utilised structured-light techniques (Gang, 2011) to reconstruct a sub-millimetre accuracy 3D model of the pipe under inspection. J. Konig et al equipped cameras and an inertial measurement unit on a hoisting cage to visually inspect a vertical mine shaft (König and O'Leary, 2020). Although robots have a precise degree of position control, the dimensions of such robots limit their abilities to be deployed in small bore pipes.…”

Section: Inspection Robotsmentioning

confidence: 99%

“…By estimating the approximate location of each image, reconstruction represents a feasible approach to localise the defects on the pipe under inspection. Implementations of such a method include the inspection of mining shafts (König and O'Leary, 2020) but also for pipes (Zhang et al, 2019;Kagami et al, 2020). Textured 3D reconstruction modelling is based on Structure from Motion (SfM) (Snavely et al, 2006).…”

Section: Rvi Approachesmentioning

confidence: 99%

“…Compared with traditional RVI inspections composed of isolated video frames, the panorama image extends the field of view and provides results with intrinsic position and dimension information that are of great utility in the production of meaningful surface condition evaluations. Such a technique has been featured in the literature on vision inspections (Xie et al, 2018;König and O'Leary, 2020). Before being stitched into a panorama image for internal surface inspections, the raw images must be unwrapped and projected onto a flat plane.…”

Section: Rvi Approachesmentioning

confidence: 99%

See 2 more Smart Citations

Meta Reinforcement Learning Based Underwater Manipulator Control

Moon

Bae²,

Cashmore

2021

2021 21st International Conference on Control, Automation and Systems (ICCAS)

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Visual inspection is one of the most ubiquitous forms of non-destructive testing, being widely used in routine pipe inspections. For small bore pipes (centimetre diameter), inspectors often have a restricted field of view limiting overall image and inspection quality. Stitching multiple unwrapped images is a common inspection technique to provide a full view inspection image by combining multiple video frames together.A key challenge of this method is knowing the camera pose of each frame. Consequently, mechanical centralisers are often utilised to ensure the camera is located centrally. For the inspection of small-bore pipes, such mechanical centralisers are often too large to fit. This paper presents a post-processing, Structure-from-Motion (SfM) based approach to unwrap and stitch inspection images, captured by a manually deployed commercial videoscope. It advances state-of-the-art approaches which rely on the projection of a laser pattern into the field of view, thus reducing the equipment size. The process consists of camera pose estimation, preliminary point cloud generation, secondary fitting, images unwrapping and stitching to form an undistorted view of the pipe interior. Two industrial focussed demonstrators verified the successful implementation for small-bore pipe inspections. Whereby the new approach does not rely on image features to create the surface texture and is less sensitive to the image quality, more areas can be retrieved from inspections. The reconstructed area was increased by up to 87% using the new approach versus the conventional 3D model.

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Section: Inspection Robotsmentioning

confidence: 99%

Section: Rvi Approachesmentioning

confidence: 99%

Section: Rvi Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Meta Reinforcement Learning Based Underwater Manipulator Control

Moon

Bae²,

Cashmore

2021

2021 21st International Conference on Control, Automation and Systems (ICCAS)

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“…This method can be stitch two or more digital images with overlapping parts into a panoramic image whose FOV is larger. It has been widely used in many applications such as mine inspection (König & O'Leary, 2020), medical treatment (Zheng et al, 2020), remote sensing (González-García et al, 2020), and 3D reconstruction (Li et al, 2019). However, when it is applied to videos from the surveillance system deployed in coal mines, the stitching technology is associated with the following problems: (1) Underexposure and overexposure due to non-uniform illumination; (2) Missing scenes due to insufficient FOV of the cameras; (3) Obliquity of the panoramic images due to pose change of the cameras.…”

Section: Introductionmentioning

confidence: 99%

Video Stitching method for a Surveillance System Deployed at a Fully Mechanized Mining Face

Li¹,

Yang²,

Mao³

et al. 2021

Preprint

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Using video stitching technology, video images with overlapping parts can be stitched into a complete image, with characteristics such as intuitiveness, visualization, and measurable analysis. This technology could be applied in the operation of coal mines for a remote monitoring and control of coal production. However, when the technology is used in coal mines, there are several challenges such as non-uniform illumination, missing scenes, and oblique panorama. In this paper, methods were purposed to solve the above problems: (1) To overcome the non-uniform illumination on a mining face, we applied the wide dynamic range technology to the images from a single camera and histogram matching algorithm on multiple images to reduce the color difference between the images; (2) To overcome the missing scene problem due to the narrow field of view (FOV) of a single camera, the SURF matching and template recognition methods are combined to achieve a stable stitching; (3) To overcome the oblique panorama issue, we applied the vertical correction technology exploiting the posture information of the camera, and then the adjacent images are concatenated. The results of practical experiments show that the proposed methods are suitable for solving the above problems in a fully mechanized mining face. The research provides a new approach for displaying extended scenes of stope faces in the intelligent collieries.

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