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| Petrov, R. H. | Madrid |
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| Casati, R. |
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| Kočí, Jan | Prague |
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Marshall, Stephen
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2023Passive gamma-ray analysis of UO2 fuel rods using SrI2(Eu) scintillators in multi-detector arrangements
- 2022X-ray classification of Special Nuclear Materials using image segmentation and feature descriptors
- 2017Automated microstructural analysis of titanium alloys using digital image processingcitations
- 2016Use of hyperspectral imaging for artwork authentication
- 2015Detection and characterisation of the solar UV network
- 2015Automated image stitching for fuel channel inspection of AGR cores
- 2013Automated image stitching for enhanced visual inspections of nuclear power stations
- 2012A review of recent advances in the hit-or-miss transformcitations
- 2011A fast method for computing the output of rank order filters within arbitrarily shaped windows
- 2007Restoration of star-field images using high-level languages and core libraries
- 2006Advances in nonlinear signal and image processing
- 2005Texture classification of grey scale corrosion images
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document
Automated image stitching for enhanced visual inspections of nuclear power stations
Abstract
In the UK, visual inspection of the fuel channels of the Advanced Gas-cooled Reactor (AGR) nuclear power stations forms an integral part of understanding the health of the reactor cores. During a statutory outage, video footage of the inside of selected fuel channels is recorded.Features of interest and anomalies are manually identified by an expert who extracts frames from the video to create a composite image for the feature of interest. This is a laborious and time consuming process which can be costly to station operators who must produce these images before returning the station to service. This paper describes an automatic technique capable of generating a 2D image of the entire internal bore of the channel. The technique uses the position of the camera coupled with advanced image processing techniques to generate a high-resolution image of the whole channel.This allows surface details to be viewed in relation to each other, and the rest of the channel, while facilitating a direct comparison of any anomalies over time. In addition, the time taken by this automated technique to produce a full core image is a fraction of that taken to manually stitch an image for a much smaller area.