Image Pre-processing Methods for Traffic Sign Recognition

Authors

  • Artjoms Suponenkovs Riga Technical University
  • Aleksandrs Glazs Riga Technical University

DOI:

https://doi.org/10.7250/tcc.2014.004

Keywords:

Adaptive binarization, computer vision, image pre-processing, segmentation, traffic sign recognition.

Abstract

The presented paper investigates the problems of image pre-processing methods for traffic sign recognition. It describes different methods and algorithms that allow to make Traffic Sign Recognition (TSR) systems adaptable for real-life environment and to convert the input information (from the camera) to a usable format for analyzing information about a traffic sign. In the experimental part of the paper the most important aspect regarding the comparison of image pre-processing algorithms is illustrated.

References

BMW Automobiles [online]. 2010. Available from: http://www.bmw.com/

Saab [online]. 2010. Available from: http://www.saab.com/

VW Media Services [online]. 2010. Available from: https://www.volkswagen-media-services.com/

J. Hatzidimos, “Automatic Traffic Sign Recognition,” Proceedings of the International Conference on Theory and Applications of Mathematics and Informatics, ICTAMI, 2004, Thessaloniki, Greece, pp. 174–184.

H. Fleyeh, “Traffic and Road Sign Recognition,” July 2008, pp. 1–255.

B. Hoferlin, K. Zimmermann, “Towards reliable traffic sign recognition”, 2009, p. 6.

A. Lorsakul, J. Suthakorn, “Traffic Sign Recognition for Intelligent Vehicle/Driver Assistance System Using Neural Network on OpenCV,” The 4th International Conference on Ubiquitous Robots and Ambient Intelligence, 2007.

R. C. Gonzalez, R. E. Woods, “Digital Image Processing 2ND EDITION,” 2002.

D. F. Rogers, J. A. Adams, “Matematical elememnts for computer graphics,” 2001.

A. Konushin, Introduction to computer vision [online]. 2012, Course pages. Available from: http://courses.graphicon.ru/main/vision

N. A. Ibraheem, M. M. Hasan, R. Z. Khan, P. K. Mishra, “Understanding Color Models: A Review,” 2011–2012.

L. G. Shapiro, G. C. Stockman, “Computer Vision,” 2006.

D. A. Forsyth, J. Ponce, “Computer Vision a modern approach,” 2004.

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Published

16.01.2015