Abstract
In this paper, a novel character recognition algorithm based on the Hidden Markov Models is proposed. Several typical character features are extracted from every character being recognized. A novel 1D multiple Hidden Markov models is constructed based on the features to recognize characters. A large number of vehicle license plate characters are used to test the performance of the algorithm. Experimental results prove that the recognition rate of this algorithm is high aiming at different kinds of character.
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© 2009 Springer-Verlag Berlin Heidelberg
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Wang, Y., Wei, X., Han, L., Wu, X. (2009). A Novel Character Recognition Algorithm Based on Hidden Markov Models. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_33
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DOI: https://doi.org/10.1007/978-3-642-05253-8_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05252-1
Online ISBN: 978-3-642-05253-8
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