Online Chinese character recognition system with handwritten Pinyin input

We have developed a novel online Chinese handwriting recognition system that can recognize a Chinese character either by its handwritten script or by its handwritten Pinyin syllable. The new system is particularly useful when the user forgets how to write the desired character or when the desired character is too complex to be written conveniently. To assure the accuracy and robustness, several classifiers with different characteristics are integrated. The experimental results show that we have achieved an accuracy of 92.5% for 6763-class freely-written Chinese characters and 87.1% for 412-class unconstrained-style Pinyin syllables.

[1]  Qiang Huo,et al.  Confidence guided progressive search and fast match techniques for high performance Chinese/English OCR , 2002, Object recognition supported by user interaction for service robots.

[2]  Brant C. White,et al.  United States patent , 1985 .

[3]  Alain Biem,et al.  Minimum classification error training for online handwritten word recognition , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.

[4]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  Yuan Yan Tang,et al.  Offline Recognition of Chinese Handwriting by Multifeature and Multilevel Classification , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Zheng Jing.  DYNAMIC COMBINATION OF MULTI CLASSIFIERS BASED ON MINIMUM COST CRITERION , 1999 .

[7]  Giovanni Seni,et al.  Non-cumulative character scoring in a forward search for online handwriting recognition , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[8]  Masaki Nakagawa,et al.  A new warping technique for normalizing likelihood of multiple classifiers and its effectiveness in combined on-line/off-line japanese character recognition , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.

[9]  Qiang Huo,et al.  High performance Chinese OCR based on Gabor features, discriminative feature extraction and model training , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[10]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[11]  Seong-Whan Lee,et al.  Nonlinear shape normalization methods for the recognition of large-set handwritten characters , 1994, Pattern Recognit..

[12]  Nei Kato,et al.  A Handwritten Character Recognition System Using Directional Element Feature and Asymmetric Mahalanobis Distance , 1999, IEEE Trans. Pattern Anal. Mach. Intell..