G. Flitton
A comparison of 3D interest point descriptors with application to airport baggage object detection in complex CT imagery
Flitton, G.; Breckon, T.P.; Megherbi, N.
Abstract
We present an experimental comparison of 3D feature descriptors with application to threat detection in Computed Tomography (CT) airport baggage imagery. The detectors range in complexity from a basic local density descriptor, through local region histograms and three-dimensional (3D) extensions to both to the RIFT descriptor and the seminal SIFT feature descriptor. We show that, in the complex CT imagery domain containing a high degree of noise and imaging artefacts, a specific instance object recognition system using simpler descriptors appears to outperform a more complex RIFT/SIFT solution. Recognition rates in excess of 95% are demonstrated with minimal false-positive rates for a set of exemplar 3D objects.
Citation
Flitton, G., Breckon, T., & Megherbi, N. (2013). A comparison of 3D interest point descriptors with application to airport baggage object detection in complex CT imagery. Pattern Recognition, 46(9), 2420-2436. https://doi.org/10.1016/j.patcog.2013.02.008
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 7, 2013 |
Online Publication Date | Feb 16, 2013 |
Publication Date | 2013-09 |
Deposit Date | Oct 1, 2013 |
Journal | Pattern Recognition |
Print ISSN | 0031-3203 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 46 |
Issue | 9 |
Pages | 2420-2436 |
DOI | https://doi.org/10.1016/j.patcog.2013.02.008 |
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