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Evaluation of Red Colour Segmentation Algorithms in Traffic Signs Detection
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2010 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

Colour segmentation is the most commonly used method in road signs detection. Road sign contains several basic colours such as red, yellow, blue and white which depends on countries. The objective of this thesis is to do an evaluation of the four colour segmentation algorithms. Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm. The processing time and segmentation success rate as criteria are used to compare the performance of the four algorithms. And red colour is selected as the target colour to complete the comparison. All the testing images are selected from the Traffic Signs Database of Dalarna University [1] randomly according to the category. These road sign images are taken from a digital camera mounted in a moving car in Sweden. Experiments show that the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm are more accurate and stable to detect red colour of road signs. And the method could also be used in other colours analysis research. The yellow colour which is chosen to evaluate the performance of the four algorithms can reference Master Thesis of Yumei Liu.

Place, publisher, year, edition, pages
Borlänge, 2010. , 48 p.
Keyword [en]
Traffic signs, Colour Segmentation, Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm, Shadow and Highlight Invariant Algorithm.
Identifiers
URN: urn:nbn:se:du-5806OAI: oai:dalea.du.se:5806DiVA: diva2:519124
Uppsok
Technology
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Available from: 2011-09-02 Created: 2011-09-02 Last updated: 2012-04-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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  • nn-NO
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Output format
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