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

Feature extraction

Pattern recognition

Convolutional neural networks

Corner detection

Data processing

Databases

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