Framework for Automatic PCB Marking Detection and Recognition for Hardware Assurance

Abstract

A Bill of Materials (BoM) is a list of all components on a printed circuit board (PCB). Since BoMs are useful for hardware assurance, automatic BoM extraction (AutoBoM) is of great interest to the government and electronics industry. To achieve a high-accuracy AutoBoM process, domain knowledge of PCB text and logos must be utilized. In this study, we discuss the challenges associated with automatic PCB marking extraction and propose 1) a plan for collecting salient PCB marking data, and 2) a framework for incorporating this data for automatic PCB assurance. Given the proposed dataset plan and framework, subsequent future work, implications, and open research possibilities are detailed.

Publication
Government Microcircuit Applications and Critical Technology Conference
Olivia Dizon-Paradis
Olivia Dizon-Paradis
Graduate Research Assistant

My research interests include artificial intelligence, machine learning, computer vision, and reinforcement learning