Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
권호 표지
DOI QR코드

DOI QR Code

Lane Positioning in Highways Based on Road-sign Tracking by Kalman Filter

칼만필터 기반의 도로표지판 추적을 이용한 차량의 횡방향 위치인식

  • Lee, Jaehong (Department of Electronic Engineering, Inha University) ;
  • Kim, Hakil (School of Information and Communication Engineering, Inha University)
  • Received : 2013.10.31
  • Accepted : 2014.03.08
  • Published : 2014.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes a method of localization of vehicle especially the horizontal position for the purpose of recognizing the driving lane. Through tracking road signs, the relative position between the vehicle and the sign is calculated and the absolute position is obtained using the known information from the regulation for installation. The proposed method uses Kalman filter for road sign tracking and analyzes the motion using the pinhole camera model. In order to classify the road sign, ORB(Oriented fast and Rotated BRIEF) features from the input image and DB are matched. From the absolute position of the vehicle, the driving lane is recognized. The Experiments are performed on videos from the highway driving and the results shows that the proposed method is able to compensate the common GPS localization errors.

Keywords

References

  1. S. Moon, S. G. Lee, J. J. Kim and B. S. Kim, "Detecting Lane Departure Based on GIS Using DGPS," Transactions of KSAE, Vol.20, No.4, pp.16-24, 2012. https://doi.org/10.7467/KSAE.2012.20.4.016
  2. A. Mogelmose, M. M. Trivedi and T. B. Moeslund, "Vision-based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey," IEEE Transactions on Pattern Recognition and Machine Intelligence, Vol.13, No.4, pp.1484-1497, 2012.
  3. Z. Hu and Y. Tsai, "A Homography-based Vision Algorithm for Traffic Sign Attribute Computation," Computer-aided Civil and Infrastructure Engineering, Vol.24, No.6, pp.385-400. 2009. https://doi.org/10.1111/j.1467-8667.2009.00598.x
  4. H. Lim, K. Deb and K. H. Jo, "Geometrical Reorientation of Distorted Road Sign using Projection Transformation for Road Sign Recognition," Journal of Institute of Control, Robotics and Systems, Vol.15, No.11, pp.1088-1095, 2009. https://doi.org/10.5302/J.ICROS.2009.15.11.1088
  5. P. G. Jimenez, S. M. Bascon, H. G. Moreno, S. L. Arroyo and F. L. Ferreras, "Traffic Sign Shape Classification and Localization Based on the Normalized FFT of the Signature of Blobs and 2D Homographies," Signal Processing, Vol.88, No.12, pp.2943-2955, 2008. https://doi.org/10.1016/j.sigpro.2008.06.019
  6. J. Miura, T. Kanda and Y. Shirai, "An Active Vision System for Real-time Traffic Sign Recognition," IEEE Intelligent Transportation Systems Proceedings, pp.52-57, 2000.
  7. H. Noh, J. Lee, D. Lim and J. Lee, "The Research of Constructing the Real-world Image Data Base for Verifying the Function and Recognition Rate of ADAS Based on Image Sensor," KSAE Annual Conference Proceedings, pp.1398-1402, 2012.
  8. J. Lee and D. Yun, "The Road Traffic Sign Recognition and Automatic Positioning for Road Facility Management," Int. J. Highw. Engineering, Vol.15, No.1, pp.155-161, 2013. https://doi.org/10.7855/IJHE.2013.15.1.155
  9. N. Otsu, "A Tlreshold Selection Method from Gray-level Histograms," IEEE Transactions on Systems, Man, and Cybernetics, Vol.9, No.1, pp.62-66, 1979. https://doi.org/10.1109/TSMC.1979.4310076
  10. C. Fang, J. Liang, C. Lo and S. Chen, "A Realtime Visual-based Front-mounted Vehicle Collision Warning System," IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, pp.1-8, 2013.
  11. E. Rublee, V. Rabaud, K. Konolige and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," IEEE International Conference on Computer Vision, pp.2564-2571, 2011.
  12. E. Rosten, R. Porter and T. Drummond, "Faster and Better: A Machine Learning Approach to Corner Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.32, No.1, pp.105-119, 2010. https://doi.org/10.1109/TPAMI.2008.275
  13. M. Calonder, V. Lepetit, M. Ozuysal and T. Trzcinski, "BRIEF: Computing a Local Binary Descriptor Very Fast," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.34, No.7, pp.1281-1298, 2012. https://doi.org/10.1109/TPAMI.2011.222
  14. J. Lee, X. Cui, H. Kim, S. Lee and H. Kim, "INHA : Localization of Mobile Robots based on Feature Matching with a Single Camera," IEEE International Conference on Systems, Man, and Cybernetics, 2013.

Cited by

  1. Corner Detection-based Road Sign Detection for Low-cost Sensor Fusion-based Precise Localization System vol.26, pp.1, 2018, https://doi.org/10.7467/KSAE.2018.26.1.020