Off-line Arabic Handwritten Isolated Character Recognition using Hidden Markov Models
نویسنده
چکیده
This paper presents a recognition system for Arabic handwritten isolated characters. The recognition system is based on hidden Markov model (HMM). The entire system is capable of recognizing the Arabic handwritten characters. First, the system removes all the variation in the character images. Second, Features are extracted using the sliding window technique with HMM. Then, the HMM is used for recognition and classification process. The Hidden Markov Model Toolkit (HTK) is used for the classification process. HTK is a special toolkit used for the purpose of speech recognition. The proposed system is applied to a database for Arabic characters. The results are superior comparing to previous conducted research.
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