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Machine Vision on FPGA for Recognition of Road Signs
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis is focused on developing a robust algorithm for recognition of road signs including all stages of a machine vision system i.e. image acquisition, pre-processing, colour segmentation, labelling and classifi-cation. Images are acquired by two different imaging systems and noise removal is done by applying Mean filter. Furthermore, different colour segmentation methods are investigated to find out the most high-performance approach and after applying dynamic segmentation based on blue channel in YCbCr colour space, the obtained binary image is transferred to a personal computer through the developed PC software using standard serial port and further processing and classification is run on the PC. Histogram of Oriented Gradients (HOG) is used as the main feature for recognition of road signs and finally the classification task is fulfilled by employing hardware efficient Minimum Distance Classifier (MDC).

Place, publisher, year, edition, pages
2012. , 87 p.
Keyword [en]
Machine Vision, FPGA, VHDL, Image Analysis, Road Sign Recognition
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:miun:diva-17370OAI: oai:DiVA.org:miun-17370DiVA: diva2:570467
Educational program
Internationellt masterprogram i elektronikkonstruktion TELAA 120 hp
Uppsok
Technology
Supervisors
Examiners
Available from: 2012-11-20 Created: 2012-11-19 Last updated: 2012-11-20Bibliographically approved

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Department of Information Technology and Media
Engineering and Technology

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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