Multi-Font Printed Tibetan Character Recognition
Ding Xiao · Zhongwen xinxi xuebao · 2003
Tibetan character recognition is a significant module of Chinese multi language information processing system,however hardly any research work has been undertaken yet. A comprehensive method based on statistical pattern recognition approach for multi font printed Tibetan character recognition is proposed. Firstly, directional line element features are extracted from the contour of input character. After feature dimension reduction by Linear Dircriminant Analysis (LDA) to formulate compact feature vector, two stage classification strategy based on confidence value is adapted to decide the category of input character. Euclidean Distance with Deviation (EDD) is designed for effective rough classification while Modified Quadratic Discriminant Function (MQDF) is employed to perform fine classification. Selecting proper classifier parameters via experiment, a recognition accuracy of 99.79% on test set containing 177,600 characters (300 samples per category) is achieved. The experimental results show the validity of proposed method.