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Comparison of Three Smart Camera Architectures for Real-time Machine Vision System
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design. (STC)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2013 (English)In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 10, Art. no. 402- p.Article in journal (Refereed) Published
Abstract [en]

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 micro-controller. 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.

Place, publisher, year, edition, pages
2013. Vol. 10, Art. no. 402- p.
Keyword [en]
Machine Vision, Component Labeling, Smart Camera
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-19953DOI: 10.5772/57135ISI: 000328072100001Scopus ID: 2-s2.0-84890537511Local ID: STCOAI: oai:DiVA.org:miun-19953DiVA: diva2:652381
Funder
Knowledge Foundation
Available from: 2013-09-30 Created: 2013-09-30 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Real-Time Optical Position Sensing on FPGA
Open this publication in new window or tab >>Real-Time Optical Position Sensing on FPGA
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2014. 95 p.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 176
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-24035 (URN)STC (Local ID)978-91-87557-29-3 (ISBN)STC (Archive number)STC (OAI)
Supervisors
Available from: 2015-01-08 Created: 2015-01-07 Last updated: 2017-03-06Bibliographically approved

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Malik, Abdul WaheedThörnberg, BennyPalaniappan, Prasanna Kumar
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