Detection and Recognition of Painted Road Surface Markings

Jack Greenhalgh, Majid Mirmehdi

Abstract

A method for the automatic detection and recognition of text and symbols painted on the road surface is presented. Candidate regions are detected as maximally stable extremal regions (MSER) in a frame which has been transformed into an inverse perspective mapping (IPM) image, showing the road surface with the effects of perspective distortion removed. Detected candidates are then sorted into words and symbols, before they are interpreted using separate recognition stages. Symbol-based road markings are recognised using histogram of oriented gradient (HOG) features and support vector machines (SVM). Text-based road signs are recognised using a third-party optical character recognition (OCR) package, after application of a perspective correction stage. Matching of regions between frames, and temporal fusion of results is used to improve performance. The proposed method is validated using a data-set of videos, and achieves F-measures of 0.85 for text characters and 0.91 for symbols.

References

  1. Bottazzi, V. S., Borges, P. V. K., and Jo, J. (2013). A visionbased lane detection system combining appearance segmentation and tracking of salient points. In 2013 IEEE Intelligent Vehicles Symposium, pages 443-448. IEEE.
  2. Chen, Z. and Ellis, T. (2013). Automatic lane detection from vehicle motion trajectories. In 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, pages 466-471. IEEE.
  3. Clark, P. and Mirmehdi, M. (2002). Recognising text in real scenes. International Journal on Document Analysis and Recognition, 4(4):243-257.
  4. Danescu, R. and Nedevschi, S. (2010). Detection and Classification of Painted Road Objects for Intersection Assistance Applications. In Proc. 13th International IEEE Conference on Intelligent Transportation Systems, pages 433 - 438.
  5. Google (2013). Tesseract-OCR. http://code.google.com/p/ tesseract-ocr/. [Online; accessed 8-October-2013].
  6. Greenhalgh, J. and Mirmehdi, M. (2012). Traffic sign recognition using MSER and random forests. In European Signal Processing Conference, pages 1935- 1939.
  7. Hanwell, D. and Mirmehdi, M. (2009). Detection of lane departure on high-speed roads. In International Conference on Pattern Recognition Applications and Methods.
  8. Huang, J., Liang, H., and Wang, Z. (2013). Robust lane marking detection under different road conditions. Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on, 1(12):1753-1758.
  9. Kheyrollahi, A. and Breckon, T. P. (2010). Automatic real-time road marking recognition using a feature driven approach. Machine Vision and Applications, 23(1):123-133.
  10. Li, Y., He, K., and Jia, P. (2007). Road markers recognition based on shape information. In Intelligent Vehicles Symposium, 2007 IEEE, pages 117-122.
  11. Merino-Gracia, C., Lenc, K., and Mirmehdi, M. (2011). A head-mounted device for recognizing text in natural scenes. In Camera-Based Document Analysis and Recognition.
  12. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., and Gool, L. V. (2005). A Comparison of Affine Region Detectors. International Journal of Computer Vision, 65(1-2):43- 72.
  13. Rebut, J., Bensrhair, A., and Toulminet, G. (2004). Image segmentation and pattern recognition for road marking analysis. In 2004 IEEE International Symposium on Industrial Electronics, pages 727-732 vol. 1. Ieee.
  14. Vacek, S., Schimmel, C., and Dillmann, R. (2007). Roadmarking Analysis for Autonomous Vehicle Guidance. EMCR, (1):1-6.
  15. Wu, T. and Ranganathan, A. (2012). A practical system for road marking detection and recognition. In 2012 IEEE Intelligent Vehicles Symposium, pages 25-30. Ieee.
  16. Zhang, F., St, H., Chen, C., Buckl, C., and Knoll, A. (2013). A lane marking extraction approach based on Random Finite Set Statistics. Intelligent Vehicles Symposium, 2013 IEEE, pages 1143-1148.
Download


Paper Citation


in Harvard Style

Greenhalgh J. and Mirmehdi M. (2015). Detection and Recognition of Painted Road Surface Markings . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 130-138. DOI: 10.5220/0005273501300138


in Bibtex Style

@conference{icpram15,
author={Jack Greenhalgh and Majid Mirmehdi},
title={Detection and Recognition of Painted Road Surface Markings},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={130-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005273501300138},
isbn={978-989-758-076-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Detection and Recognition of Painted Road Surface Markings
SN - 978-989-758-076-5
AU - Greenhalgh J.
AU - Mirmehdi M.
PY - 2015
SP - 130
EP - 138
DO - 10.5220/0005273501300138