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Generalized Architecture for a Real-time Computation of an Image Component Features on a FPGA
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media. (STC)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media. (STC)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media. (STC)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media. (STC)ORCID iD: 0000-0002-3429-273X
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper describes a generalized architecture for real-time component labeling and computation of image component features. Computing real-time image component features is one of the most important paradigms for modern machine vision systems. Embedded machine vision systems demand robust performance, power efficiency as well as minimum area utilization. The presented architecture can easily be extended with additional modules for parallel computation of arbitrary image component features. Hardware modules for component labeling and feature calculation run in parallel. This modularization makes the architecture suitable for design automation. Our architecture is capable of processing 390 video frames per second of size 640x480 pixels. Dynamic power consumption is 24.20mW at 86 frames per second on a Xilinx Spartran6 FPGA.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-14536OAI: oai:DiVA.org:miun-14536DiVA: diva2:443685
Projects
STC
Available from: 2011-09-26 Created: 2011-09-26 Last updated: 2013-11-11Bibliographically approved
In thesis
1. Machine vision architecture on FPGA
Open this publication in new window or tab >>Machine vision architecture on FPGA
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2012. 111 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 82
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-16698 (URN)STC (Local ID)978-91-87103-16-2 (ISBN)STC (Archive number)STC (OAI)
Available from: 2012-08-10 Created: 2012-08-10 Last updated: 2016-10-20Bibliographically approved

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Abdul Waheed, MalikThörnberg, BennyCheng, XinLawal, NajeemImran, Muhammad

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CiteExportLink to record
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Citation style
  • apa
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