Abstract
In this paper, we propose an analytical approach of an offline recognition of handwritten Arabic. Our method is based on Markov modeling and takes into account the characteristic of the Arabic script.
The objective is to propose a methodology for rapid implementation of our approach. To this end, a preprocessing phase that can prepare the data was introduced. These data are then used by two methods of feature extraction: The first is the use of a sliding window on binary images to recognize words from right to left. The second is the use of the. The results of this step are converted to data sequence as vectors that are combined through a multi-stream.
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Maqqor, A., Halli, A., Satori, K., Tairi, H. (2013). A Slippery Window and VH2D Approach to Recognition Offline Arabic Words. In: Nagamalai, D., Kumar, A., Annamalai, A. (eds) Advances in Computational Science, Engineering and Information Technology. Advances in Intelligent Systems and Computing, vol 225. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00951-3_26
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DOI: https://doi.org/10.1007/978-3-319-00951-3_26
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00950-6
Online ISBN: 978-3-319-00951-3
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