Preprocessing of digital images in systems of location and recognition of road signs
P.Yu. Yakimov

PDF, 876 kB

Full text of article: Russian language.

DOI: 10.18287/0134-2452-2013-37-3-401-405

Pages: 401-405.

Abstract:
The problem of localization and recognition of road signs is actual for today. Such a system can not only improve safety, compensating the probable human inattention, but it also helps to reduce tiredness, helping drivers keep an eye on the surrounding traffic conditions. This article proposes an efficient algorithm for preprocessing digital images for further detection of road signs in real time. The article considers the possibility of using HSV color space to extract the red. A denoising algorithm was developed to improve the accuracy and speed of detection. Parallel implementation on the GPU was used to remove the noise. The resulting images are best suited for further localization of road signs.

Key words:
HSV color space, image denoising, traffic signs detection, traffic signs recognition, CUDA.

References:

  1. Shneier, M. Road sign detection and recognition // Proc. IEEE Computer Society Int. Conf. on Computer Vision and Pattern Recognition. – 2005 – P. 215–222.
  2. Nikonorov, A. Traffic sign detection on GPU using color shape regular expressions / A. Nikonorov, P. Yakimov, P. Maksimov // VISIGRAPP IMTA-4 2013. – 2013. – Paper Nr 8.
  3. Ruta, A. A New Approach for In-Vehicle Camea Traffic Sign Detection and Recognition / A. Ruta, F. Porikli, Y. Li, S. Watanabe, H. Kage, K. Sumi // IAPR Conference on Machine vision Applications (MVA), Session 15: Machine Vision for Transportation – May 2009.
  4. Belaroussi, R. Road Sign Detection in Images / R. Belaroussi, P. Foucher, J.P. Tarel, B. Soheilian, P. Charbonnier, N. Paparoditis // A Case Study, 20th International Conference on Pattern Recognition (ICPR) – 2010. – P. 484-488.
  5. Tkalcic, M. Colour spaces - perceptual, historical and applicational background / M. Tkalcic, J. Tasic, // In The IEEE Region 8 EUROCON 2003 proceedings – 2003. – P. 304-308.

  6. Koschan, A. Digital Color Image Processing / A. Koschan, M.A. Abidi // ISBN 978-0-470-14708-5. – 2008. – 376 p.
  7. Travis, D. Effective Color Displays Theory and Practice // Academic Press, ISBN 0-12-697690-2. – 1991. – 328 p.
  8. Chen, S.Y. Boosted Road Sign Detection And Recognition / Sin-Yu Chen, Jun-Wei Hsieh // International Conference on Machine Learning and Cybernetics – 2008. – Vol. 7. – P. 3823-3826.
  9. Ruta, A. Detection, Tracking and Recognition of Traffic Signs from Video Input / A. Ruta, Y. Li, X. Liu // Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems, Beijing, China, 2008.
  10. Yakimov, P. Detection and color correction of artifacts in digital images / S. Bibikov, R. Zakharov, A. Nikonorov, V. Fursov, P. Yakimov // Optoelectronics, Instrumentation and Data Processing. – 2011. – Vol. 47, issue 3. – P. 226-232.
  11. Yakimov, P. Investigation of the efficiency of CUDA technology in the problem of distributed prepress of digital images / S.A. Bibikov, A.V. Nikonorov, V.A. Fursov, P.Y. Yakimov // conference Science in the Internet: scalability, parallelism, efficiency. – 2009. – P. 21-26. – (In Russian).
  12. Yakimov, P. Software for image processing using massively multithreaded CUDA environment / P.Y. Yakimov, V.A. Fursov // conference "Conducting research in the field of information and telecommunication technologies". – 2010. – P. 119-120. – (In Russian).

© 2009, IPSI RAS
Institution of Russian Academy of Sciences, Image Processing Systems Institute of RAS, Russia, 443001, Samara, Molodogvardeyskaya Street 151; e-mail: ko@smr.ru; Phones: +7 (846 2) 332-56-22, Fax: +7 (846 2) 332-56-20