Airport security officers scan luggage containing your clothes, toiletries and other carry-on items to spot potential bombs and weapons. The scanning machines produce X-rays and allow the screeners to view a computer-generated image that shows different materials as varying colors on the image. If a suspicious material stands out, the luggage may be subject to additional screening, like a manual search. The problem is that the images are not always clear and can be difficult to interpret. A team of researchers from Cranfield University and Nottingham Trent University is trying to solve this issue.
The new machine they are working on allows them to see the shapes of objects as well as their density, and it can identify the precise materials they’re made from. This information could improve how efficiently and accurately screeners can search for potentially dangerous items.
To test their theory, they asked 31 airport screeners to visually inspect X-ray images of simulated luggage. They were given two different instructions, and the results showed that the ability to distinguish everyday objects in X-ray images from novel prohibited items correlates with their sensitivity to false alarms. This suggests that knowing what common items look like in X-ray images facilitates their detection as recently found by Hattenschwiler et al.
The technology isn’t ready for commercial use, but it could eventually provide a more effective and efficient alternative to manual searches. One hurdle is that a human operator needs to look at all the different images and separate them to find the object of interest, which takes time. The goal is to automate the process, which would allow airports to increase the number of luggage scanned per hour.
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