NDLI: The impact of color composition on X-ray image interpretation in aviation security screening

Content Provider	IEEE Xplore Digital Library
Author	von Bastian, C.C. Schwaninger, A. Michel, S.
Copyright Year	2009
Description	Author affiliation: University of Applied Sciences Northwestern Switzerland, School of Applied Psychology, Institute Human in Complex Systems, 4600 Olten, Switzerland (Schwaninger, A.; Michel, S.) \|\| Department of Psychology, University of Zurich, Switzerland (von Bastian, C.C.)
Abstract	In order to improve aviation security, many airports apply Threat Image Projection (TIP) and computer-based X-ray image interpretation training (CBT). One difference between TIP and CBT X-ray images is the algorithm used to merge virtual threat items into X-ray images of passenger bags, resulting in different color nuances. In this study, we tested the influence of merging algorithms on threat object detection performance, reaction time and confidence rating of 12 airport security screeners. The image merging algorithms of the individually adaptive CBT X-Ray Tutor were used. We have found that the hit rate was higher for TIP images compared to CBT images. Accordingly, the mean of confidence ratings was increased for TIP images. The reaction times tended to be shorter for TIP images. The results of our study indicate that the CBT merging algorithm used in this study is more realistic than the tested TIP image merging algorithm.
Starting Page	201
Ending Page	205
File Size	691423
Page Count	5
File Format	PDF
ISBN	9781424441693
DOI	10.1109/CCST.2009.5335539
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-05
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	X-ray imaging Airports Merging Object detection Psychology Humans Image recognition Computer security Testing Displays image merging algorithms aviation security display technologies humanmachine interaction object recognition
Content Type	Text
Resource Type	Article

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