@article{(Open Science Index):https://publications.waset.org/pdf/4689,
	  title     = {Ottoman Script Recognition Using Hidden Markov Model},
	  author    = {Ayşe Onat and  Ferruh Yildiz and  Mesut Gündüz},
	  country	= {},
	  institution	= {},
	  abstract     = {In this study, an OCR system for segmentation,
feature extraction and recognition of Ottoman Scripts has been
developed using handwritten characters. Detection of handwritten
characters written by humans is a difficult process. Segmentation and
feature extraction stages are based on geometrical feature analysis,
followed by the chain code transformation of the main strokes of
each character. The output of segmentation is well-defined segments
that can be fed into any classification approach. The classes of main
strokes are identified through left-right Hidden Markov Model
(HMM).},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {2},
	  year      = {2008},
	  pages     = {462 - 464},
	  ee        = {https://publications.waset.org/pdf/4689},
	  url   	= {https://publications.waset.org/vol/14},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 14, 2008},
	}