TY - JFULL AU - Ayşe Onat and Ferruh Yildiz and Mesut Gündüz PY - 2008/3/ TI - Ottoman Script Recognition Using Hidden Markov Model T2 - International Journal of Computer and Information Engineering SP - 461 EP - 464 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/4689 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 14, 2008 N2 - 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). ER -