Off-line handwritten Chinese character recognition with hidden Markov models
Bing Feng, Xiao Qing Ding · 2002
Off-line handwritten Chinese character recognition is one of the most difficult tasks of optical character recognition because of complexity of patterns, large quantity of classes, many uncertainties, etc. The hidden Markov model (HMM) method has achieved great success in the field of speech recognition. It also exhibits potential advantage in degraded text and handwritten character recognition. We present a modeling and recognition method of off-line handwritten Chinese character with hidden Markov models and its experimental result.