Semi-synchronous hybrid detection algorithm for event-based sensing

One problem encountered during algorithm development for autonomous event-based imaging systems is the tradeoff between optical task performance and overall system latency. To address such problems, this research proposes a new algorithm designed to process event-based data with real-time capability on limited computing hardware. The algorithm consists of two main steps: an event-space sorting and data reduction step to quickly determine regions of interest (ROIs) in a discretized set of imagery data and a frame-space final decision step applying computationally complex algorithms to the ROIs to determine if a target is present. Results include performance in both laboratory and simulated settings to attain robust assessment of the algorithm’s performance. Successful implementation provides processing rates sufficient for real-time system operations while retaining effective optical task performance.