Browsing by Author "Megherbi, Najla"
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Item Open Access A 3D extension to cortex like mechanisms for 3D object class recognition(2012-06-21T00:00:00Z) Flitton, Greg T.; Breckon, Toby P.; Megherbi, NajlaWe introduce a novel 3D extension to the hierarchical visual cortex model used for prior work in 2D object recognition. Prior work on the use of the visual cortex standard model for the explicit task of object class recognition has solely concentrated on 2D imagery. In this paper we discuss the explicit 3D extension of each layer in this visual cortex model hierarchy for use in object recognition in 3D volumetric imagery. We apply this extended methodology to the automatic detection of a class of threat items in Computed Tomography (CT) security baggage imagery. The CT imagery suffers from poor resolution and a large number of artefacts generated through the presence of metallic objects. In our examination of recognition performance we make a comparison to a codebook approach derived from a 3D SIFT descriptor and demonstrate that the visual cortex method out-performs in this imagery. Recognition rates in excess of 95% with minimal false positive rates are demonstrated in the detection of a range of threat itemsItem Open Access A comparison of 3D interest point descriptors with application to airport baggage object detection in complex CT imagery(Elsevier, 2013-02-16) Flitton, Greg T.; Breckon, Toby P.; Megherbi, NajlaWe 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.Item Open Access A comparison of classification approaches for threat detection in CT based baggage screening(IEEE, 2013-02-21) Megherbi, Najla; Han, Jiwan; Breckon, Toby P.; Flitton, Greg T.Computed Tomography (CT) based baggage security screening systems are of increasing use in transportation security. The ability to automatically identify potential threat item is a key aspect of current research in this area. Here we present a comparison of varying classification approaches for the automated detection of threat objects in cluttered 3D CT imagery from such security screening systems. By combining 3D medical image segmentation techniques with 3D shape classification and retrieval methods we compare five varying final classification stage approaches and present significant performance achievements in the automated detection of specified exemplar items.Item Open Access A novel intensity limiting approach to Metal Artefact Reduction in 3D CT baggage imagery(IEEE, 2013-02-21) Mouton, Andre; Megherbi, Najla; Flitton, Greg T.; Bizot, Suzanne; Breckon, Toby P.This paper introduces a novel technique for Metal Artefact Reduction (MAR) in the previously unconsidered context 3D CT baggage imagery. The output of a conventional sinogram completion-based MAR approach is refined by imposing an upper limit on the intensity of the corrected images and by performing post-filtering using the non-local means filter. Furthermore, performance is evaluated using a novel quantitative analysis technique, using the ratio of noisy 3D SIFT detection points identified, as well as a standard qualitative comparison (visual quality). The objective of the quantitative analysis is to evaluate the impact of MAR on the application of computer vision techniques for automatic object recognition. The study yields encouraging results in both the qualitative and quantitative analyses. The proposed method yields a significant improvement in performance when compared to algorithms based on linear interpolation and reprojection-reconstruction; especially in terms of reducing the occurrence of new artefacts in the corrected images. The results serve as a strong indication that MAR will aid human and computerised analyses of 3D CT baggage imagery for transport security screening.