Abstract
In this paper a hybrid neuro-fuzzy system for the real-time recognition of the road-signs is presented. For tracking an improvement to the continuously adaptive mean shift method is proposed. It consists in substitution of the probabilistic density for the especially formed membership function. Classification of binary pictograms of the detected signs is done with the kernel morphological neural network which is robust to noise, missing data, and small geometrical deformations of the patterns.
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Cyganek, B. (2008). Neuro-fuzzy System for Road Signs Recognition. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87536-9_52
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DOI: https://doi.org/10.1007/978-3-540-87536-9_52
Publisher Name: Springer, Berlin, Heidelberg
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