基于混合神经网络和小波变换的手写体识别

S. Sadkhan, Sabiha F. Jawad- SMIEEE
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引用次数: 5

摘要

本文将人工神经网络(ANN)和小波变换(WT)应用于手写体字符识别问题。应用Kohenen ACON型人工神经网络(ANN)设计了一个处理这一问题的识别系统模型。特征提取过程使用了WT (Haar类型)。它用于提取手写字符的参数特征。该系统使用一个130人的数据库来实现,数据库中的70个样本用于训练,所有130个样本用于系统测试。用识别率测试了该系统的有效性,结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Handwritten Recognition based on Hybrid ANN and Wavelet Transformation
This paper provides the application of Artificial Neural Network (ANN) and Wavelet Transformation (WT) into the problem of handwritten character recognition. The Design of a recognition system model that handle this problem based on applying Artificial Neural Network (ANN) of Kohenen ACON type. The feature extraction process made use of WT (the Haar Type). It’s used to extract the parametric features of the handwritten characters. The system was implemented using a database of 130 persons, 70 sample from the database were used for training, and the all 130 samples were used for testing the system. The efficiency of the system was tested using the Recognition Rate, and the results were promising.
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