Abstract
This paper presents a cascaded system for recognition of the circular road-signs. The system consists of two compound detectors-classifiers. Each operates on the Gaussian scale-space and does template matching in the log-polar domain. The first module is responsible for detection of the potential sign areas at the coarsest level of the pyramid. The second one, in turn, refines the already found places at the finest level. Thanks to this composition, as well as to the efficient matching in the log-polar domain, the system is very robust in terms of recognition of the signs with different scales and rotations, as well as under partial occlusions, poor illumination conditions, and noise.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Amit, Y.: 2D Object Detection and Recognition. MIT Press, Cambridge (2002)
Aoyagi, Y., Asakura, T.: A study on traffic sign recognition in scene image using genetic algorithms and neural networks. In: IEEE Conf. Electronics, Control, pp. 1838–1843 (1996)
Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic Detection and Recognition of Signs From Natural Scenes. IEEE Trans. on Image Proc. 13(1), 87–99 (2004)
Cyganek, B.: Soft System for Road Sign Detection. Accepted to the IFSA – Theory and Applications of Fuzzy Logic and Soft Computing, Cancun, Mexico, (June 18-21, 2007)
Cyganek, B.: Rotation Invariant Recognition of Road Signs with Ensemble of 1-NN Neural Classifiers. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds.) ICANN 2006. LNCS, vol. 4132, pp. 558–567. Springer, Heidelberg (2006)
Cyganek, B.: Recognition of Road Signs with Mixture of Neural Networks and Arbitration Modules. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3973, pp. 52–57. Springer, Heidelberg (2006)
Cyganek, B.: Matching of the Multi-channel Images with Improved Nonparametric Transformations and Weighted Binary Distance Measures. In: Reulke, R., Eckardt, U., Flach, B., Knauer, U., Polthier, K. (eds.) IWCIA 2006. LNCS, vol. 4040, pp. 74–88. Springer, Heidelberg (2006)
Cyganek, B.: Hardware-Software System for Acceleration of Image Processing Operations. Accepted to be published in the Machine Graphics & Vision (2007)
DaimlerChrysler, The Thinking Vehicle (2002), http://www.daimlerchrysler.com
Escalera, A., Armingol, J.A.: Visual Sign Information Extraction and Identification by Deformable Models. IEEE Tr. On. Int. Transportation Systems 5(2), 57–68 (2004)
Forsyth, D., Ponce, J.: Computer Vision. In: A Modern Approach, Prentice-Hall, Englewood Cliffs (2003)
Kara, L.B., Stahovich, T.F.: An image-based, trainable symbol recognizer for hand-drawn sketches. Computers & Graphics 29(4), 501–517 (2005)
Piccioli, G., Micheli, E.D., Parodi, P., Campani, M.: Robust method for road sign detection and recognition. Image and Vision Computing 14, 209–223 (1996)
Porikli, F.: Integral Histogram: A FastWay to Extract Histograms in Cartesian Spaces. TR2005-057, Mitsubishi Electric Research Laboratories, Cambridge, MA, USA (2005)
Wandell, B.A.: Foundations of Vision. Sinauer Associates Publishers Inc., Sunderland (1995)
Zheng, Y.J., Ritter, W., Janssen, R.: An adaptive system for traffic sign recognition. In: Proc. IEEE Intelligent Vehicles Symp., pp. 165–170 (1994)
Zokai, S., Wolberg, G.: Image Registration Using Log-Polar Mappings for Recovery of Large-Scale Similarity. IEEE Transactions on Image Processing 14(10), 1422–1433 (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Cyganek, B. (2007). Road Signs Recognition by the Scale-Space Template Matching in the Log-Polar Domain. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_43
Download citation
DOI: https://doi.org/10.1007/978-3-540-72847-4_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72846-7
Online ISBN: 978-3-540-72847-4
eBook Packages: Computer ScienceComputer Science (R0)