Advanced Road Vanishing Point Detection by Using Weber Adaptive Local Filter

  • Xue Fan
  • Yunfan Chen
  • Jingchun Piao
  • Irfan Riaz
  • Han Xie
  • Hyunchul Shin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10036)

Abstract

Variations in road types and its ambient environment make the single image based vanishing point detection a challenging task. Since only road trails (e.g. road edges, ruts, and tire tracks) would contribute informative votes to vanishing point detection, the Weber adaptive local filter is proposed to distinguish the road trails from background noise, which is envisioned to reduce the workload and to eliminate uninformative votes introduced by the background noise. This is possible by controlling the number of neighbors and by increasing the sensitivity for small values of the local excitation response. After road trail extraction, the generalized Laplacian of Gaussian (gLoG) filters are applied to estimate the texture orientation of those road trail pixels. Then, the vanishing point is detected based on the adaptive soft voting scheme. The experimental results on the benchmark dataset demonstrate that the proposed method is about 2 times faster in detection speed and outperforms by 1.3% in detection accuracy, when compared to the complete texture based gLoG method, which is a well-known state-of-the-art approach.

Keywords

Vanishing point Weber adaptive local filter Generalized Laplacian of Gaussian (gLoG) filter Voting map 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Xue Fan
    • 1
  • Yunfan Chen
    • 1
  • Jingchun Piao
    • 1
  • Irfan Riaz
    • 1
  • Han Xie
    • 1
  • Hyunchul Shin
    • 1
  1. 1.Department of Electronics and Communication EngineeringHanyang UniversityAnsanRepublic of Korea

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