Abstract
A vision based traffic sign recognition system collects information about road signs and helps the driver to make timely decisions, making driving safer and easier. This paper deals with the real-time detection and recognition of traffic signs from video sequences using colour information. Support vector machine based classification is employed for the detection and recognition of traffic signs. The algorithms implemented are tested in a real time embedded environment. The algorithms are trainable to detect and recognize important prohibitory and warning signs from video captured in real-time.
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Kumaraswamy, R., Prabhu, L.V., Suchithra, K., Pai, P.S.S. (2011). SVM Based Classification of Traffic Signs for Realtime Embedded Platform. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22726-4_36
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DOI: https://doi.org/10.1007/978-3-642-22726-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22725-7
Online ISBN: 978-3-642-22726-4
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