The purpose of this research is to improve the recognition rate of online Arabic handwriting recognition using HMM (Hidden Markov Model). Delayed strokes are removed from the online Arabic word to avoid the difficulty and the confusion caused by the delayed strokes in the recognition process. A new technique for extracting offline features by dividing the image into non-uniform horizontal segments is presented. The integration between online and offline approaches has proven to give a better performance. With the combination we could increase the system performance over the best individual recognizer by 2.38%.
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