High-throughput anomaly detection in document envelopes with 3D millimeter wave imaging

Andrew A. Ganse; Christine Madden; Claire M. Watts; Andreas Pedross-Engel; Matthew S. Reynolds

doi:10.1117/12.2587522

12 April 2021 High-throughput anomaly detection in document envelopes with 3D millimeter wave imaging

Andrew A. Ganse, Christine Madden, Claire M. Watts, Andreas Pedross-Engel, Matthew S. Reynolds

Proceedings Volume 11745, Passive and Active Millimeter-Wave Imaging XXIV; 117450G (2021) https://doi.org/10.1117/12.2587522
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

Non-paper inclusions inside paper and plastic document mailing envelopes present both economic loss and security concerns for shipping carriers. Such contraband often goes unnoticed unless an envelope is physically opened by a human, which is infeasible given a global shipping volume in the tens of millions of envelopes per day. Millimeter waves (mmWaves) penetrate most non-metallic packaging materials, enabling the detection of anomalous nonpaper items within a stack of documents. At the same time, the non-ionizing nature of mmWave energy enables the safe use of mmWave imaging in close proximity to human workers without a requirement for shield barriers. We demonstrate a high-throughput K-Band (24 GHz) mmWave imaging system used to scan envelopes and thin packages transiting a conveyor belt. This imaging system is capable of supporting conveyor speeds of up to 3 m/s and enables non-destructive imaging inside sealed envelopes. We also present an automated screening algorithm that uses a logistic regression approach to detect anomalies among the expected paper documents. Automatic anomaly detection removes the human from the equation and allows for high-throughput diversion of suspect envelopes for secondary screening. In this work, we investigate mmWave detection of non-paper inclusions such as metalized plastic and metal items among paper documents in paper, cardboard, and Tyvek envelopes, as well as padded bubble packs. We achieve resolution better than 1 cm in the plane of the envelope, allowing for identification of sub-cm3 anomalies, and demonstrate automated first-pass flagging of suspect envelopes.

Conference Presentation

Citation Download Citation

Andrew A. Ganse, Christine Madden, Claire M. Watts, Andreas Pedross-Engel, and Matthew S. Reynolds "High-throughput anomaly detection in document envelopes with 3D millimeter wave imaging", Proc. SPIE 11745, Passive and Active Millimeter-Wave Imaging XXIV, 117450G (12 April 2021); https://doi.org/10.1117/12.2587522

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available