Hardware-Accelerated Machine Vision using Field-Programmable Gate Arrays (FPGA)

John R. Haughery, Iowa State University
Justin E. Noronha, Iowa State University

This abstract is published as Haughery, J. R., Noronha, J.E., "Hardware-Accelerated Machine Vision using Field-Programmable Gate Arrays (FPGA)," 2016 ATMAE Annual Conference, Orlando, FL. Nov. 2-5, 2016. Posted with permission.

Abstract

Summary: A hardware-accelerated vision system for object tracking was developed and implemented using FPGAs. Based on Amdahl’s Law equation, the final hardware design outperformed a similar software implementation by a factor of 7.7.