Automatic Detection and Recognition of Symbols and Text on the Road Surface

  • Jack GreenhalghEmail author
  • Majid Mirmehdi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9493)


This paper presents a method for the automatic detection and recognition of text and symbols on the road surface, in the form of painted road markings. Candidates for road markings are detected as maximally stable extremal regions (MSER) in an inverse perspective mapping (IPM) transformed version of the image, which shows the road surface with the effects of perspective distortion removed. Separate recognition stages are then used to recognise words and symbols. Recognition of text-based regions is performed using a third-party optical character recognition (OCR) package, after application of a perspective correction stage. Symbol-based road markings are recognised by extracting histogram of oriented gradient (HOG) features, which are then classified using a support vector machine (SVM) classifier. The proposed method is validated using a data-set of videos, and achieves F-measures of 0.85 for text characters and 0.91 for symbols.


Computer vision Machine learning Text recognition Intelligent transportation systems 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Visual Information LaboratoryUniversity of BristolBristolUK

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