Comparison of Three Smart Camera Architectures for Real-Time Machine Vision System

This paper presents a machine vision system for real-time computation of distance and angle of a camera from a set of reference points located on a target board. Three different smart camera architectures were explored to compare performance parameters such as power consumption, frame speed and latency. Architecture 1 consists of hardware machine vision modules modeled at Register Transfer (RT) level and a soft-core processor on a single FPGA chip. Architecture 2 is commercially available software based smart camera, Matrox Iris GT. Architecture 3 is a two-chip solution composed of hardware machine vision modules on FPGA and an external microcontroller. Results from a performance comparison show that Architecture 2 has higher latency and consumes much more power than Architecture 1 and 3. However, Architecture 2 benefits from an easy programming model. Smart camera system with FPGA and external microcontroller has lower latency and consumes less power as compared to single FPGA chip having hardware modules and soft-core processor.