@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}, }