Printed Noisy Greek Characters Recognition Using Hidden Markov Model, Kohonen Network, K Nearest Neighbours and Fuzzy Logic
Salouan S. Safi, Belaid Bouikhalene · International Journal of Signal Processing Image Processing and Pattern Recognition · 2015
In this paper, we present for printed multi-oriented, multi-scaled and noisy Greek characters recognition a comparison in terms of precision, rapidity and stability between several classifiers which the first one is a probabilistic that is hidden Markov model, the second is a neuronal that is Kohonen network or self-organizing maps while the rest of other classifiers are based on a combination between these both classifiers and even more a statistical method that is K nearest neighbors in their tree different versions which are majority voting, weighted distances and fuzzy.For this purpose we have for preprocessed each character image by the median filter and the thresholding technique, then in order to extract efficiently their features, we have exploited the Krawtchouk invariant moments.