1 July 2004 Improving the detection of low-density weapons in x-ray luggage scans using image enhancement and novel scene-decluttering techniques
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J. of Electronic Imaging, 13(3), (2004). doi:10.1117/1.1760571
Abstract
Very few image processing applications have dealt with x-ray luggage scenes in the past. Concealed threats in general, and low-density items in particular, pose a major challenge to airport screeners. A simple enhancement method for data decluttering is introduced. Initially, the method is applied using manually selected thresholds to progressively generate decluttered slices. Further automation of the algorithm, using a novel metric based on the Radon transform, is conducted to determine the optimum number and values of thresholds and to generate a single optimum slice for screener interpretation. A comparison of the newly developed metric to other known metrics demonstrates the merits of the new approach. On-site quantitative and qualitative evaluations of the various decluttered images by airport screeners further establishes that the single slice from the image hashing algorithm outperforms traditional enhancement techniques with a noted increase of 58% in low-density threat detection rates.
Besma R. Abidi, Jimin Liang, Mark Mitckes, Mongi A. Abidi, "Improving the detection of low-density weapons in x-ray luggage scans using image enhancement and novel scene-decluttering techniques," Journal of Electronic Imaging 13(3), (1 July 2004). http://dx.doi.org/10.1117/1.1760571
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KEYWORDS
Image segmentation

Image enhancement

X-rays

Image processing

X-ray imaging

Radon transform

Weapons

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