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WASHINGTON, USA – Limited access to high-quality data has long slowed the development of faster, more accurate baggage screening systems at airports.
The Department of Homeland Security (DHS) Science and Technology Directorate (S&T) is tackling this challenge by launching a first-of-its-kind dataset of 250 synthetic carry-on baggage images. This initiative supports the president’s executive orders to secure public safety and improve trade and travel, while helping innovators accelerate the creation of next-generation screening technology.
“Detection algorithms are key to reducing false alarms that cause hands-on bag inspections and longer checkpoint wait times,” said Pedro Allende, DHS under secretary for science and technology. “Enabling rapid algorithm development from the best innovators not only will increase detection accuracy at the checkpoint but also improve the traveller experience.”
“Currently, only a limited number of images of curated bags are available to train carry-on baggage algorithms, and developers must complete a vetting process to view them, which is prohibitive for some,” said screening at speed program manager, Dr John Fortune.
To address this, Cignal LLC of Reedsville, Pennsylvania, developed synthetic images for S&T’s Screening at Speed Program. The dataset, available by request on Cignal’s website, includes 250 computed tomography (CT) X-ray images that mirror the high-resolution scans produced by the Transportation Security Administration’s latest detection systems. Future releases may feature larger, more complex bag sets and synthetic millimeter wave images for training passenger screening systems.
The images will be released in Digital Imaging and Communication in Medicine (DICOM) format, familiar to algorithm developers across industries.