Under the sponsored research fund by MSRA, a research team from the Human-Computer Intelligent Interface Lab (http://www.hcii-lab.net) of Souch China University of Technology (SCUT) has explored several new modular technologies for high performance handwritten Chinese character recognition and calligraphic beautification of handwritten Chinese characters. Two significant achievements have been accomplished by SCUT team.

Achievement 1. Building Compact MQDF Classifier for Large Character Set Recognition by Subspace Distribution Sharing

The SCUT research team has proposed a method for building compact and high accuracy MQDF classifier. Quadratic classifier with modified quadratic discriminant function (MQDF) has been successfully applied to recognition of handwritten characters to achieve very high performance. By using a small set of prototypes clustered from the original subspaces to represent the uncompressed sub-vectors, the storage of the MQDF parameters is greatly compressed. By seeking for the optimal tradeoff curves between parameter size and recognition accuracy, some sets of parameter settings are discovered to form the optimal compact dictionary for MQDF parameters. The fast recognition speed (1.8ms/char for PC and 64ms/char for Pocket PC) and compact dictionary size (2.06MB) make the high accuracy MQDF classifier become practical for memory limited hand-held devices such as PDAs, mobile phones and Pocket PCs.

Achievement 2. Calligraphic Beautification of Handwritten Chinese Characters

SCUT team focus on a patternized approach in attempting beautification of handwritten Chinese characters through feature corresponding and fusing. Simulated Analogous Reasoning Process is employed in the proposed system to adopt some certain styles onto users’ input characters. The system is made applicable by accommodating to common variations in handwritings. The verification-based stroke corresponding algorithm allows inputs that contain connected or falsely-separated strokes. Also, the tri-unit stroke model which handles the connection parts between successive strokes ensures a natural simulation and beautification for the connection parts expressly, and thus better preserves reflections of user individualities. The proposed system is proved to be effective and feasible on transfiguring handwritings and preserving originality of users’ in series of experiments.