Novel Data Visualizations of X-Ray Data for Aviation Security Applications using the OTAP Platform

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2016-01-01
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Gittinger, Jaxon
Jimenez, Edward
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Review of Progress in Quantitative Nondestructive Evaluation
Center for Nondestructive Evaluation

Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.

This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.

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This work will demonstrate the implementation of a traditional and non-traditional visualization of x-ray images for aviation security applications that will be feasible with the Open Threat Assessment Platform (OTAP). Anomalies of interest to aviation security are fluid, where characteristic signals of anomalies of interest can evolve rapidly. OTAP is an open architecture baggage screening prototype that allows 3rd-party vendors to develop and easily implement detection algorithms and specialized hardware on a field deployable screening technology. In this study, stereoscopic images were created using an unmodified, field-deployed system and rendered on the Oculus Rift, a commercial virtual reality video gaming headset. The example described in this work is not dependent on the Oculus Rift, and is possible using any comparable hardware configuration capable of rendering stereoscopic images. The depth information provided from viewing the images will aid the detection of characteristic signals from anomalies of interest. If successful, OTAP has the potential to allow for aviation security to become more fluid in its adaptation to the evolution of anomalies of interest. This work demonstrates one example that is easily implemented using the OTAP platform, that could lead to the future generation of ATR algorithms and data visualization approaches.

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