Abstract
A fast method for the recognition and classification of informational traffic signs is presented in this paper. The aim is to provide an efficient framework which could be easily used in inventory and guidance systems. The process consists of several steps which include image segmentation, sign detection and reorientation, and finally traffic sign recognition. In a first stage, a static HSI colour segmentation is performed so that possible traffic signs can be easily isolated from the rest of the scene; secondly, shape classification is carried out so as to detect square blobs from the segmented image; next, each object is reoriented through the use of a homography transformation matrix and its potential axial deformation is corrected. Finally a recursive adaptive segmentation and a SVM-based recognition framework allow us to extract each possible pictogram, icon or symbol and classify the type of the traffic sign via a voting-scheme.
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Vázquez-Reina, A., López-Sastre, R.J., Siegmann, P., Lafuente-Arroyo, S., Gómez-Moreno, H. (2006). An Approach to the Recognition of Informational Traffic Signs Based on 2-D Homography and SVMs. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_106
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DOI: https://doi.org/10.1007/11864349_106
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44630-9
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