Abstract
In this paper, we propose an analytical approach of an offline recognition of handwritten Arabic. Our method is based on Hidden Markov Models (HMM) Toolkit (HTK), modeling type that takes into consideration the characteristics of Arabic script and possible inclinations of cursive words. 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 an extraction method of two groups of the characteristics (Features of Local Densities and Features Statistical) with the use of the technique of sliding windows, the results of this step are processed in sequence information as vectors to HTK (Hidden Markov Model Toolkit).
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
