Robust recognition of printed Chinese characters using multilayer perceptron and Walsh functions

Kou-Yuan Huang; Hsiang-Tsun Yen

doi:10.1117/12.139986

16 September 1992 Robust recognition of printed Chinese characters using multilayer perceptron and Walsh functions

Kou-Yuan Huang, Hsiang-Tsun Yen

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.139986
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

In this paper, a neural network approach for the recognition of printed Chinese characters is developed. A multi-layer perceptron is trained as the classifier by using the back-propagation algorithm, and the Walsh functions are employed for feature extraction. Thirty similar Chinese characters (classes) are designed in the experimental domain. The network is initially trained with noisefree training samples, and is retrained gradually with misclassified noisy testing patterns to improve the robustness of the classifier. Through classifying a large set of 9000 unknown testing patterns of various noise degrees, a great augmentation in system robustness and an encouraging recognition performance are presented.

Citation Download Citation

Kou-Yuan Huang and Hsiang-Tsun Yen "Robust recognition of printed Chinese characters using multilayer perceptron and Walsh functions", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.139986

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