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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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.
© (2004) Society of Photo-Optical Instrumentation Engineers (SPIE)
Besma R. Abidi, Besma R. Abidi, Jimin Liang, Jimin Liang, Mark Mitckes, Mark Mitckes, Mongi A. Abidi, 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). https://doi.org/10.1117/1.1760571 . Submission:
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