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Journal of Electronic Imaging

Improving the detection of low-density weapons in x-ray luggage scans using image enhancement and novel scene-decluttering techniques
Author(s): Besma R. Abidi; Jimin Liang; Mark Mitckes; Mongi A. Abidi
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Paper 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.

Paper Details

Date Published: 1 July 2004
PDF: 16 pages
J. Electron. Imaging. 13(3) doi: 10.1117/1.1760571
Published in: Journal of Electronic Imaging Volume 13, Issue 3
Show Author Affiliations
Besma R. Abidi, Univ. of Tennessee/Knoxville (United States)
Jimin Liang, Xidian Univ. (China)
Mark Mitckes, Univ. of Tennessee/Knoxville (United States)
Mongi A. Abidi, Univ. of Tennessee/Knoxville (United States)


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