This post is also available in: heעברית (Hebrew)

An algorithm-based software innovation could significantly improve the efficiency of cargo X-ray screening process, detecting possible threats in aircraft cargo, despite complex X-ray images.

Air Cargo skids and pallets take up a large amount of space on every commercial passenger flight. Federal law requires this cargo be screened at the same level as checked baggage.  Single and dual energy X-ray systems can be scaled up to screen air cargo skids, but they produce two-dimensional views of air cargo that are often difficult for screeners to interpret due to the complexity of the content’s image.

As result, many skids are broken down into smaller configurations or single packages and screened individually. The US Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and the Transportation Security Administration (TSA) are collaborating to address these challenges.

Increases in computing power, algorithmic complexity, and machine learning capabilities offer opportunities to enhance current X-ray screening capabilities and reduce the amount of time to break down and reassemble transported cargo.  

The Opacity and Complexity Analysis Software Tool (OCAST) is an automatic algorithm that analyzes an image and provides an operator a description of the complexity of the image.  The operator can use that score plus their own view of the image to determine whether to pass the cargo or investigate further, as reported by newswise.com.

The system gives the operator a simple interface with a red/yellow/green color report.  A red light means the cargo should be inspected a second time (breaking the skid down). Yellow indicates the software is not sure of a threat, and the operator should investigate further before making a decision. Green means the cargo’s image is clearly seen, and if the operator does not see another reason for concern, the cargo does not need to be broken down.

The next step is the integration of this software with a full-sized skid scanning machine, provided by Astrophysics. A laboratory demonstration is planned for 2019.  Future development will include improvements to the algorithms to eliminate uncertain “yellow light” returns and field testing a full-skid scanner integrated with OCAST.

OCAST will start working in June 2019 to support TSA air cargo screening efforts. It will provide low-cost enhancement to many screening facilities as the cost of distributing software and performing the necessary system upgrades is minimal.