Abstract: In this paper we present a new approach in Tifinagh character recognition using a combination of, k-nearest neighbor algorithm and the bigram language model. After the preprocessing of the text image, and the word segmentation, for each image character, the k-NN algorithm proposes candidates weighted of their membership degree. Then we use the bigram language model to choose the most appropriate sequence of characters. Results show that our method increases the recognition rate.

Said Gounane, Mohammad Fakir and Belaid Bouikhalen, “Handwritten Tifinagh Text Recognition Using Fuzzy K-NN and Bi-gram Language Model” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Selected Papers from Third international symposium on Automatic Amazigh processing SITACAM13, 2013. http://dx.doi.org/10.14569/SpecialIssue.2013.030206

@article{Gounane2013,
title = {Handwritten Tifinagh Text Recognition Using Fuzzy K-NN and Bi-gram Language Model},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Selected Papers from Third international symposium on Automatic Amazigh processing SITACAM13}
doi = {10.14569/SpecialIssue.2013.030206},
url = {http://dx.doi.org/10.14569/SpecialIssue.2013.030206},
year = {2013},
publisher = {The Science and Information Organization},
volume = {3},
number = {2},
author = {Said Gounane and Mohammad Fakir and Belaid Bouikhalen},
}