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Proceedings Paper

A vehicle threat detection system using correlation analysis and synthesized x-ray images
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Paper Abstract

The goal of the proposed research is to automate the vehicle threat detection with X-ray images when a vehicle crosses the country border or the gateway of a secured facility (military base). The proposed detection system requires two inputs: probe images (from X-ray machine) and gallery images (from database). For each vehicle, the gallery images include the X-ray images of fully-loaded (with typical cargo) and unloaded (empty) vehicle. The proposed system produces two types of outputs for threat detection: the detected anomalies and the synthesized images (e.g., grayscale fusion, color fusion, and differential images). The anomalies are automatically detected with the block-wise correlation analysis between two temporally aligned images (probe versus gallery). The locations of detected anomalies can be marked with small rectangles on the probe X-ray images. The several side-view images can be combined into one fused image in gray scale and in colors (color fusion) that provides more comprehensive information to the operator. The fused images are suitable for human analysis and decision. We analyzed a set of vehicle X-ray images, which consists of 4 images generated from AS and E OmniView Gantry™. The preliminary results of detected anomalies and synthesized images are very promising; meanwhile the processing speed is very fast.

Paper Details

Date Published: 7 June 2013
PDF: 10 pages
Proc. SPIE 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII, 87090V (7 June 2013); doi: 10.1117/12.2016646
Show Author Affiliations
Yufeng Zheng, Alcorn State Univ. (United States)
Adel Elmaghraby, Univ. of Louisville (United States)


Published in SPIE Proceedings Vol. 8709:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII
J. Thomas Broach; Jason C. Isaacs, Editor(s)

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