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A Fast Pavement Location Approach for Autonomous Car Navigation

  • Thiago Rateke
  • Karla A. Justen
  • Vito F. Chiarella
  • Rodrigo T. F. Linhares
  • Antonio Carlos Sobieranski
  • Eros Comunello
  • Aldo von Wangenheim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8827)

Abstract

This paper describes a fast image segmentation approach designed for pavement detection in a moving camera. The method is based on a graph-oriented segmentation approach where gradient information is used temporally as a system of discontinuities to control merging between adjacent regions. The method presumes that the navigable path usually is located at specific positions on the scene, and a predefined set of seed points is used to locate the region of interest. The obtained results shown the proposed approach is able to accurately detect in an inexpensive computation manner the navigable path even in non-optimum scenarios such as miss-painted or unpaved dirt roads. Validation was conducted using a dataset with 701 samples of navigable paths, presenting a very high precision for real-time applications.

Keywords

Image Segmentation Seed Point Gradient Information Concrete Paver Pattern Recognition Letter 
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 2014

Authors and Affiliations

  • Thiago Rateke
    • 1
    • 2
  • Karla A. Justen
    • 2
  • Vito F. Chiarella
    • 2
  • Rodrigo T. F. Linhares
    • 1
  • Antonio Carlos Sobieranski
    • 2
    • 3
  • Eros Comunello
    • 1
    • 2
  • Aldo von Wangenheim
    • 1
    • 2
    • 3
  1. 1.Graduate Program in Computer ScienceFederal University of Santa CatarinaBrazil
  2. 2.Laboratory of Image Processing and Computer GraphicsNational Brazilian Institute for Digital ConvergenceBrazil
  3. 3.Department of InformaticsFederal University of ParanaBrazil

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