Abstract
For the first time in this paper, directional traffic signs feature extracting based on Pulse Coupled Neural Network (PCNN) in different color space are investigated. Entropy series is extracted from the image of traffic sign in both RGB model and HSV model. Each entropy series of R, G, B, H, S, V color space is used as feature vector for recognition, match analysis is carried out by minimum variance. Experiments are carried out based on the directional signs class in national standard GB5768-1999 database. Experiment results show that feature vector based on Entropy series in B color space get the higher recognition rates than the other color space, with 50 iteration and 5 × 5 convolution kernel matrix of PCNN.
Project supported by College Technology and Research Youth Foundation of Hebei Province (No. 2010121).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Merve, C.K., Muthittin, G., Sima, E.U.: Traffic sign recognition using Scale invariant feature transform and color classification. In: 23rd International Symposium on Computer and Information Sciences, pp. 1–6. IEEE Press, New York (2008)
Joshi, M., Gingh, M.J., Dalela, S.: Automatic Colored Traffic Sign Detection using Optoelectronic Correlation Architectures. In: IEEE International Conference on Vehicular Electronics and Safety, pp. 75–78. IEEE Press, New York (2008)
King, H.L.: Intra color-shape classification for traffic sign recognition. In: International Computer Symposium, pp. 642–647 (2010)
Chen, H.B., Wang, Q., Xu, X.R., et al.: Line detection in traffic sign image based on improved Hough transforms. Opt. Precision Eng. 17(5), 1111–1118 (2009)
Andrey, V., Jo, K.H.: Automatic Detection and Recognition of Traffic Signs using Geometric Structure Analysis. In: International Joint Conference on SICE-ICASE, pp. 1451–1456 (2006)
Rughooputh, S.D.D.V., Buootun, H., Rughooputh, H.C.S.: Pulse coupled neural networks for sign recognition for navigation. In: IEEE International Conference on Industrial Technology, vol. 1, pp. 89–94. IEEE Press, New York (2003)
Wang, Z.H.B., Ma, Y.D., Cheng, F.Y., et al.: Review of pulse-coupled neural networks. Image and Vision Computing 28(10), 5–13 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, M., Yang, L., Wang, X., Liu, J. (2012). Investigation of Directional Traffic Sign Feature Extracting Based on PCNN in Different Color Space. In: Wang, F.L., Lei, J., Lau, R.W.H., Zhang, J. (eds) Multimedia and Signal Processing. CMSP 2012. Communications in Computer and Information Science, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35286-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-35286-7_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35285-0
Online ISBN: 978-3-642-35286-7
eBook Packages: Computer ScienceComputer Science (R0)