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Proceedings Paper

Neural-network-assisted drug detection in x-ray images
Author(s): Narbik Manukian; John L. Kirkwood; Gregg D. Wilensky; JungChou Chang
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Paper Abstract

A drug detection system using neural networks is applied to the problem of detecting cocaine stimulants in backscatter and transmission images of baggage generated by the AS and E 101 x-ray mobile van. This system automatically locates and evaluates potential targets of interest by merging intensity and geometric data form backscatter and transmission x-ray images and outlines the suspicious regions in red. Two neural networks are used to analyze the combination of both backscatter and transmission data; the first network analyzes suspicious regions from the images and outputs a probability that the region contains drugs, and the second integrates all such regions from a bag and outputs a probability that the bag contains drugs. The system performance approaches that of expert human operators in detecting drugs. It can benefit inspection by reducing the number of bags that the human needs to inspect thereby increasing the number of bags that a human can process in a given time.

Paper Details

Date Published: 3 April 1997
PDF: 10 pages
Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271739
Show Author Affiliations
Narbik Manukian, Logicon R&D Associates (United States)
John L. Kirkwood, Logicon R&D Associates (United States)
Gregg D. Wilensky, Logicon R&D Associates (United States)
JungChou Chang, Logicon R&D Associates (United States)


Published in SPIE Proceedings Vol. 3078:
Wavelet Applications IV
Harold H. Szu, Editor(s)

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