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Comparison of Three Smart Camera Architectures for Real-Time Machine Vision System
Author(s) -
Aqsa Malik,
Benny Thörnberg,
Prasanna Kumar
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/57135
Subject(s) - computer science , smart camera , field programmable gate array , microcontroller , embedded system , frame rate , computer hardware , latency (audio) , machine vision , hardware architecture , software , artificial intelligence , telecommunications , programming language
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

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