Journal of Information Processing
The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line Cursive Kanji Character Recognition Using Stroke-Based Affine Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper describes an optimal stroke-correspondence search method that makes possible stroke-order-free on-line character recognition. During the stroke-correspondence search process, conventional individual stroke-information regarding the shape and position of each stroke, and interstroke-information regarding the mutual relationships among strokes are both employed. The optimal path search for stroke-correspondence, being based on an optimal criterion including both intra- and interstroke-information, is systematically carried out. The reasonable level stroke-correspondence search is achieved partially by using the information regarding the actually occurring stroke-order, which does not hinder the framework of stroke-order-free recognition due to its use of statistically stable information. A large improvement in both computational time and recognition-accuracy were achieved in the current experiments.