Two-tier self-organizing visual model for road sign recognition

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 794-799

  Nguwi, Yok Yen ^a   Cho, Siu Yeung ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Gabor feature; Road sign recognition; Self organizing map; Visual model

Indexed keywords

CONFORMAL MAPPING; FEATURE EXTRACTION; IMAGE ENHANCEMENT; MAPS; NEURAL NETWORKS; OPTICAL PROJECTORS; SELF ORGANIZING MAPS; VIDEO SIGNAL PROCESSING; VISUAL COMMUNICATION;

COGNITIVE PROCESSES; CORTICAL MAPS; GABOR FEATURE; GABOR WAVELETS; HIT RATES; HUMAN BRAINS; PRIMARY VISUAL CORTICES; ROAD SIGN RECOGNITION; ROAD SIGN RECOGNITIONS; ROAD SIGNS; SELF-ORGANIZING; SELF-ORGANIZING MAP; TEST SETS; TOPOLOGICAL MAPS; UNSUPERVISED APPROACHES; VISUAL CORTICES; VISUAL INFORMATIONS; VISUAL MODEL; VISUAL MODELS;

ROADS AND STREETS;

EID: 56349131286     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4633887     Document Type: Conference Paper

References (26)

1. P. Paclik, "Road Sign Recognition Survey," [Online]. Available: http://euler.fd.cvut.cz/research/rs2/files/sk.oda-rs-survey.html
2. Image Recognition Laboratory in University of Koblenz-Landau, [Online], Available: http://www.un.i-koblenz.de/FB4/Institutes/ICV/AGPriese/Research
3. L. Priese, J. Klieber, R. Lakmann, V. Rehrmann and R. Schian, "New Results on Traffic Sign Recognition," in Proc. of the Intelligent Vehicles Symposium, 1994, pp. 249-254.
4. Intelligent Transportation Systems at the Carlos 111 University of Madrid, [Online]. Available: http://www.uc3m.es/uc3m/dpto/IN/dpin04/ISL/SIT_eng. html.
5. A. Soetedjo and K. Yamada, "Traffic sign classification using ring partitioned method," IEICE Trans. Fundamentals, vol. E88A, no. 9, pp. 166-178, Sep 2005.
6. H. Fleyeh, S. Gilani, and M. Dougherty, "Road sign detection and recognition using Fuzzy ARTMAP: A case study Swedish speed-limit signs," in Proc. of Artificial Intelligence and Soft Computing, 2006.
7. P. Paclik, J. Novovicova, P. Pudil, and P.Somol, "Road Sign Classification using the Laplace Kernel Classifier," Pattern Recognition Letters, 21 (13-14) 1165-1173, 2000.
8. M. Lalonde and Y. Li, "Road sign recognition-Survey of the state of art," Technical Report for Sub-Project 2.4, Centre de recherche informatique de Montreal, CRIM-IIT-95/09-35, 1995.
9. th Int. Conf. on Image Analysis and Processing, Palermo, Italy, 2001, pp. 572-577.
10. D.L. Kellmeyer, and H.T. Zwahlen, "Detection of Highway Warning Signs in Natural Video Images Using Color Image Processing and Neural Networks," Proc. IEEE Int. Conf. on Neural Networks, 7: pp. 4226-4231, 1994.
11. D.M. Gavrila and V. Philomin, "Real-time object detection for smart vehicles," Proc. of IEEE Int. Conf. on Computer Vision, Greece, pp. 87-93, 1999.
12. G. Loy and N. Barnes, "Fast shape-based road sign detection for a driver assistance system," in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 1, 2004, pp. 70-75.
13. P. Paclik and J. Novovicova, "Road Sign Classification without Colour Information," Proc. of 6th Conf. of Advanced School of Imaging and Computing, ASCI, Lomniel, Belgium, 2000.
14. J. Daugman, "Uncertainty relation for resolution in space, spatial. frequency, and orientation optimized by two-dimensional visual cortical filters," J. Opt. Soc. Amer., vol. 2, no. 7, pp. 1160-1169, 1985.
15. Haykin, S.S., Neural Networks: a comprehensive foundation. 2nd ed. 1999, Upper Saddle River, N.J.: Prentice Hall, xxi, 842 p. Chapter 9, pp. 443
16. L. G. Shapiro and G. C. Stockman, Computer Vision. Prentice Hall, January 23, 2001.
17. D. Hubel and T. Wiesel, "Receptive fields, binocular interaction, and functional architecture in the cat's visual cortex," J. Physiol. (London), vol. 160, pp. 106-154, 1962.
18. G.E. La Cara, M. Ursino, "A Neural. Network Model of Contours Extraction Based on Orientation Selectivity in the Primary Visual Cortex: Applications on Real Images", Proc. 26th Annual Intl. Conf. of the IEEE EMBS, September 2004.
19. G.E. La Cara, M. Ursino, M. Bettini "Extraction of Salient Contours in Primary Visual Cortex: A Neural Network Model Based on Physiological Knowledge", Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International. Conference of the IEEE, Volume 3, 17-21 Sept. 2003 pp. 2242-2245 Vol.3.
20. J.P. Jones, L.A. Palmer, "An evaluation of the Two-Dimensional Gabor Filter model of simple Receptive fields in cat striate cortex", J.Neurophysiol., vol. 58 (6), pp. 1233-1258, 1987.
21. Berkes, P. and Wiskott, L. (2002). Applying Slow Feature Analysis to Image Sequences Yields a Rich Repertoire of Complex Cell Properties.,in Artificial Neural. Networks - ICANN 2002 pp. 81-86, Springer 2002
22. Yok-Yen Nguwi, and Abbas Kouzani, "Automatic Road Sign Recognition Using Neural. Networks," proc of International Joint Conference on Neural Networks, pp 7686-7693, 2006
23. A. de la Escalera and P. Radeva, "Fast, greyscale road sign model matching and recognition," Recent Advances in Artificial Intelligence Research and Development, J. Vitria et. al, (Eds.) IOS Press, 2004, pp. 69-76.
24. J. Torresen, J. Bakke, and L. Sekanina, "Efficient recognition of speed limit signs," in Proc. of the 7th Int. IEEE Conf. on Intelligent Transportation Systems, 2004, pp. 652 - 656.
25. X. Gao, N. Shevtsova, K. Hong, S. Batty, L. Podladchikova, A. Golovan, D. Shaposhnikov, and V. Gusakova, "Vision, models based identification of traffic signs," in Proc. of the 1 st Europ. Conf. on Color in Graphics, Image and Vision, France, 2002, pp. 47-51.
26. S. Vitabile, A. Gentile, and F. Sorbello, "A neural network based automatic road signs recognizer," in Proc. of the 2002 International Joint Conference on Neural Networks, vol. 3, 2002, pp. 2315-2320.