The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-line recognition of handprinted characters: survey and beta tests
Pattern Recognition
A Shape Analysis Model with Applications to a Character Recognition System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using grammars for pattern recognition in images: A systematic review
ACM Computing Surveys (CSUR)
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An application of combined statistical and structural-syntactic approach in Chinese character recognition is presented. The algorithm adopts a structural representation for Chinese characters, but in the classification and training process, the structural matching and parameter adjustment is conducted in a statistical way. Different from the conventional structural approaches, in this system, only a few predefined "knowledge" is required. In most cases, knowledge acquisition is simplified to "memorization" of examples, and the parameters for classification can be refined using statistical training. In this way it avoids the main difficulties inherent in the implementation of classification systems based on structural features. Compared with conventional statistical algorithms, the algorithm is based on a structural model of image patterns, so it has approximately all the advantages of structural pattern recognition algorithms. A prototype system has been realized based on this strategy, and the effectiveness of the method is verified by the experimental results.