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http://dx.doi.org/10.7848/ksgpc.2015.33.6.595

Automatic Extraction of Route Information from Road Sign Imagery  

Youn, Junhee (Korea Institute of Civil Engineering and Building Technology, ICT Convergence and Integration Research Institute)
Chong, Kyusoo (Korea Institute of Civil Engineering and Building Technology, ICT Convergence and Integration Research Institute)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.33, no.6, 2015 , pp. 595-603 More about this Journal
Abstract
With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.
Keywords
Big Data; Road Sign; Route Number; Route Number Type; Direction Information;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 Broggi, A., Cerri, P., Medici, P., Porta, P., and Ghisio, G. (2007), Real time road signs recognition, Proceedings of the 2007 IEEE Intelligent Vehicles Symposium, IEEE, 13- 15 June, Istanbul, Turkey, pp. 981-986.
2 Chong, K. (2014), Text area detection of road sign images based on IRBP method, The Journal of the Korea Institute of Intelligent Transport Systems, Vol. 13, No. 6, pp. 1-9. (in Korean with English abstract)   DOI
3 Gonzalez, A., Bergasa, L.M., Yebes, J., and Almazan, J. (2012), Text recognition on traffic panels from street-level imagery, 2012 Intelligent Vehicles Symposium, 3-7 June, Alcala de Henares, Spain, pp. 340-345.
4 Gonzalez, R.C. and Wood, R.E. (1992), Digital Image Processing, Addison-Wesley Publishing Company, pp. 484-485
5 Huang, X., Liu, K., and Zhu, L. (2012), Auto scene text detection based on edge and color features, 2012 International Conference on Systems and Informatics, 19-20 May, Yantai, China, pp. 1882-1886.
6 Kim, G., Chong, K., and Youn, J. (2013), Automatic recognition of direction information in road sign image using OpenCV, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 31, No. 4, pp. 293-300. (in Korean with English abstract)   DOI
7 Sastre, R.J.L., Arroyo, S.L., Siegmann, P., Jimenez, P.G., and Reina, A.V. (2005), Recognition of mandatory traffic signs using the hausdorff distance, Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artifical Vision, 15-17 September, Malta, pp. 216-221.
8 Lee, T., Lim, K., Bae, G., Byun, H., and Choi, Y. (2015), An illumination invariant traffic sign recognition in the driving environment for intelligent vehicles, Journal of KIISE, Vol. 42, No. 2, pp. 203-212. (in Korean with English abstract)   DOI
9 Lee, J.S. and Yun, D.G. (2013), The road traffic sign recognition and automatic positioning for road facility management, International Journal Highway Engineering, Vol. 15, No. 1, pp. 155-161.   DOI
10 MOLIT (2014), Road sign regulation, Ministry of Land, Infrastructure and Transport, (last date accessed: 1 November 2015).
11 Soetedjo, A., Yamada K., and Limpraptono, F.Y. (2010), Segmentation of road guidance sign symbols and characters based on normalized RGB chromaticity diagram, International Journal of Computer Applications, Vol. 3, No. 3, pp. 10-15.   DOI
12 Vavilin A. and Jo, K.H. (2009), Graph-based approach for robust road guidance sign recognition from differently exposed images, Journal of Universal Computer Science, Vol. 15, No. 4, pp. 786-804.
13 Wikipedia (2015), Tesseract, https://en.wikipedia.org/wiki/Tesseract_(software) (last date accessed: 21 November 2015).
14 Willis, N. (2006), Google’s Tesseract OCR engine is a quantum leap forward, http://archive09.linux.com/articles/57222 (last date accessed: 18 October 2015).
15 Zakir, U. (2011), Automatic Road Sign Detection and Recognition, Ph.D. dissertation, Loughborough University, United Kingdom.
16 Benallal, M. and Meunier, J. (2003), Real-time color segmentation of road signs, IEEE CCECE 2003 Canadian Conference on Electrical and Computer Engineering, IEEE, 4-7 May, Vol. 3, pp. 1823-1826.
17 Bascon, S.M., Arroyo, S.L., Siegmann, P.H., Moreno, G., and Rodriguez, F.J.A. (2008), Traffic sign recognition system for inventory purposes, IEEE Intelligent Vehicles Symposium Eindhoven University of Technology Eindhoven, IEEE, 4-6 June, Eindhoven, Netherlands, pp. 590-595.