Detection and Recognition of Road Markings in Panoramic Images

  • Cheng Li
  • Ivo Creusen
  • Lykele Hazelhoff
  • Peter H. N. de With
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9009)


The detection of road lane markings has many practical applications, such as advanced driver assistance systems and road maintenance. In this paper we propose an algorithm to detect and recognize road lane markings from panoramic images. Our algorithm consists of four steps. First, an inverse perspective mapping is applied to the image, and the potential road markings are segmented based on their intensity difference compared to the surrounding pixels. Second, we extract the distance between the center and the boundary at regular angular steps of each considered potential road marking segment into a feature vector. Third, each segment is classified using a Support Vector Machine (SVM). Finally, by modeling the lane markings, previous false positive detected segments can be rejected based on their orientation and position relative to the lane markings. Our experiments show that the system is capable of recognizing \(93\,\%\), \(95\,\%\) and \(91\,\%\) of striped line segments, blocks and arrows respectively, as well as \(94\,\%\) of the lane markings.


Support Vector Machine Panoramic Image Advance Driver Assistance System Lane Marking Road Marking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Cheng Li
    • 1
    • 2
  • Ivo Creusen
    • 1
    • 2
  • Lykele Hazelhoff
    • 1
    • 2
  • Peter H. N. de With
    • 1
    • 2
  1. 1.Cyclomedia TechnologyZaltbommelThe Netherlands
  2. 2.Eindhoven University of TechnologyEindhovenThe Netherlands

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