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Traffic Sign detection and recognition
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2017 (English)In: Computer Vision and Imaging in Intelligent Transportation Systems, John Wiley & Sons, 2017, 1, 343-374 p.Chapter in book (Refereed)
Abstract [en]

This chapter presents an overview of traffic sign detection and recognition. It describes the characteristics of traffic signs and the requirements and difficulties when dealing with traffic sign detection and recognition in outdoor images. The chapter also covers the different techniques invoked to segment traffic signs from the different traffic scenes and the techniques employed for the recognition and classification of traffic signs. It points many problems regarding the stability of the received colour information, variations of these colours with respect to the daylight conditions, and absence of a colour model that can led to a good solution. It also proposes an adaptive colour segmentation model based on Neural Networks. The chapter demonstrates the way to classify segmented traffic signs by employing one of widely used classifiers, AdaBoost , based on a set of features, in this case HOG descriptors, which was developed for pedestrian recognition but found the way for many applications in different fields. The chapter ends by showing examples where traffic sign recognition is applicable in vehicle industry

Place, publisher, year, edition, pages
John Wiley & Sons, 2017, 1. 343-374 p.
Keyword [en]
Traffic sign, recognition, classification, color segmentation, SOM, HOG
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-25069ISBN: 9781118971604 (print)OAI: oai:DiVA.org:du-25069DiVA: diva2:1103608
Available from: 2017-05-30 Created: 2017-05-30 Last updated: 2017-05-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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