Abstract
This paper presents a novel color-based method to detect road signs directly from videos. A road sign usually has specific colors and high contrast to its background. Traditional color-based approaches need to train different color detectors for detecting road signs if their colors are different. This paper presents a novel color model derived from Karhunen-Loeve(KL) transform to detect road sign color pixels from the background. The proposed color transform model is invariant to different perspective effects and occlusions. Furthermore, only one color model is needed to detect various road signs. After transformation into the proposed color space, a RBF (Radial Basis Function) network is trained for finding all possible road sign candidates. Then, a verification process is applied to these candidates according to their edge maps. Due to the filtering effect and discriminative ability of the proposed color model, different road signs can be very efficiently detected from videos. Experiment results have proved that the proposed method is robust, accurate, and powerful in road sign detection.
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Escalera, A.D.L., et al.: Road Traffic Sign Detection and Classification. IEEE Transaction on Industrial Electronics 44(6), 848–859 (1997)
Kehtarnavaz, N., Ahmad, A.: Traffic sign recognition in noisy outdoor scenes. In: Proceedings of Intelligent Vehicles 1995 Symposium, pp. 460–465 (September 1995)
Fang, C.-Y., Chen, S.-W., Fuh, C.-S.: Road-sign detection and tracking. IEEE Transactions on Vehicular Technology 52(5), 1329–1341 (2003)
Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic detection and recognition of signs from natural scenes. IEEE Transactions on Image Processing 13(1), 87–99 (2004)
Loy, G., Barnes, N.: Fast shaped-based road sign detection for a Driver Assistance System. In: IROS 2004 (2004)
Wu, W., Chen, X., Yang, J.: Detection of Text on Road Signs From Video. IEEE Transactions on ITS 6(4), 378–390 (2005)
Barnes, N., Zelinsky, A.: Real-time radial symmetry for speed sign detection. In: Proc. IEEE Intelligent Vehicles Symposium, Italy, pp. 566–571 (June 2004)
Bahlmann, C., et al.: A system for traffic sign detection, tracking, and recognition using color, shape, and motion information. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 255–260 (June 2005)
de Saint Blancard, M.: Road Sign Recognition: A Study of Vision-based Decision Making for Road Environment Recognition, ch. 7. Springer, Heidelberg (1991)
Healey, G.: Segmenting Images Using Normalized Color. IEEE Transactions on Systems, Man, and Cybernetics 22(1), 64–73 (1992)
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© 2007 Springer-Verlag Berlin Heidelberg
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Tsai, LW., Tseng, YJ., Hsieh, JW., Fan, KC., Li, JJ. (2007). Road Sign Detection Using Eigen Color. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_15
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DOI: https://doi.org/10.1007/978-3-540-76386-4_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76385-7
Online ISBN: 978-3-540-76386-4
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