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Diagonally-reinforced Lane Detection Scheme for High-performance Advanced Driver Assistance Systems

  • Park, Mingu (Namyang R&D Center, Hyundai Motors) ;
  • Yoo, Kyoungho (Samsung SDS) ;
  • Park, Yunho (Department of Electronics and Communications Engineering, Kwangwoon University) ;
  • Lee, Youngjoo (Department of Electronic Engineering, Kwangwoon University)
  • Received : 2016.10.05
  • Accepted : 2017.02.03
  • Published : 2017.02.28

Abstract

In this paper, several optimizations are proposed to enhance the quality of lane detection algorithms in automotive applications. Considering the diagonal directions of lanes, the proposed limited Hough transform newly introduces image-splitting and angle-limiting schemes that relax the number of possible angles at the line voting process. In addition, unnecessary edges along the horizontal and vertical directions are pre-defined and removed during the edge detection procedures, increasing the detecting accuracy remarkably. Simulation results shows that the proposed lane recognition algorithm achieves an accuracy of more than 90% and a computing speed of 92 frame/sec, which are superior to the results from the previous algorithms.

Keywords

References

  1. H. Yoo, U. Yang and K. Sohn, "Gradientenhancing conversion for illumination-robust lane detection," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, pp. 1083-1094, Sep. 2013. https://doi.org/10.1109/TITS.2013.2252427
  2. M. B. de Paula and C. Jung, "Automatic detection and classification of road lane markings using onboard vehicular cameras," IEEE Trans. Intell. Transp. Syst., vol. 16, no. 6, pp. 3160-3169, Dec. 2015. https://doi.org/10.1109/TITS.2015.2438714
  3. S. Jung, J. Youn and S. Sull, "Efficient lane detection based on spatiotemporal images," IEEE Trans. Intell. Transp. Syst., vol. 17, no. 1, pp. 289-295, Jan. 2016. https://doi.org/10.1109/TITS.2015.2464253
  4. K.-Y. Chiu and S.-F. Lin, "Lane detection using color-based segmentation," in Proc. IEEE Intell. Veh. Symp., 2005, pp. 706-711.
  5. P. Chanawangsa and C. W. Chen, "A new colorbased lane detectio vis Gaussian radial basis function networks," in Proc. Int. Conf. Conneted Vehicles and Expo (ICCVE), 2012, pp. 166-171.
  6. Z. Kim, "Robust lane detection and tracking in challenging scenarios," IEEE Trans. Intell. Transp. Syst., vol. 9, no. 1, pp. 16-26, Jan. 2008. https://doi.org/10.1109/TITS.2007.908582
  7. J. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679-695, June 1986. https://doi.org/10.1109/TPAMI.1986.4767851
  8. V. Gaikwad and S. Lokhande, "Lane departure identification for advanced drier assistance," IEEE Trans. Intell. Transp. Syst., vol. 16, no. 2, pp. 910-917, Apr. 2015. https://doi.org/10.1109/TITS.2014.2347400
  9. S. B. Yacoub and J. M. Jolion, "Hierachical line extraction," IEE Proc. Vis. Image Signal Process., vol. 142, no. 1, pp. 7-14, 1995. https://doi.org/10.1049/ip-vis:19951434
  10. R. K. Satzoda, S. Sathyanarayana, T. Srikanthan and S. Sathyanarayana, "Hierarchical additive Hough transform for lane detection," IEEE Embedded Syst. Lett., vol. 2, no. 2, pp. 23-26, Feb. 2010. https://doi.org/10.1109/LES.2010.2051412