I. Methasate and S. Sae-Tang (Thailand)
On-line Character Recognition, Thai, HMM, Stroke segmentation.
This paper describes the On-line Thai character recognition system which used the segmented stroke information by Hidden Markov Model (HMM). Firstly, the stroke sequences are smoothened and unnecessary coordinates are removed. Secondly, the strokes are divided into sub-stroke and then merge some short stroke if necessary. In this step, the features of sub-stroke are extracted. Finally, the feature vectors are recognized by Hidden Markov Model. In applying free-hand Thai single characters to the system, it gives the average recognition rates of 92.17 %.
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