Pyramid multiresolution classifier for online large vocabulary Chinese character recognition

Quen-Zong Wu; I-Chang Jou; Yann Le Cunn

doi:10.1117/12.206703

21 April 1995 Pyramid multiresolution classifier for online large vocabulary Chinese character recognition

Quen-Zong Wu, I-Chang Jou, Yann Le Cunn

Proceedings Volume 2501, Visual Communications and Image Processing '95; (1995) https://doi.org/10.1117/12.206703
Event: Visual Communications and Image Processing '95, 1995, Taipei, Taiwan

Abstract

A pyramid classifier is proposed for large vocabulary Chinese characters, which at first uses low resolution features to roughly classify the input character, and then used higher resolution features to make finer classification stage by stage. In addition to the rule- based preclassification, there are three stages to achieve recognition. The number of candidate categories is reduced step by step. We use one thousand categories of Chinese characters for experiments. Simulation results show that this classifier can recognize the input character with 93.1% and 90% accuracy on the training set and the test set respectively.

Citation Download Citation

Quen-Zong Wu, I-Chang Jou, and Yann Le Cunn "Pyramid multiresolution classifier for online large vocabulary Chinese character recognition", Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); https://doi.org/10.1117/12.206703

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