基于多字体基本特征的人工神经网络字符识别

E. Neves, A. Gonzaga, A. Slaets
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引用次数: 11

摘要

神经网络为字符识别问题提供了另一种方法。本文介绍了一种基于拓扑特征提取的多字体字符识别系统的开发。通过适当指定一组特征,如垂直、水平和倾斜笔划、曲率、开放和封闭区域,这里称为“基本特征”,使用反向传播神经网络进行识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-font character recognition based on its fundamental features by artificial neural networks
Neural networks present an alternative approach for the character recognition problem. This paper describes the development of a recognition system of multi-font character using topological feature extraction to recognize capital isolated letters. By properly specifying a set of features such as vertical, horizontal, and slant strokes, curvature, open and closed areas, called here "fundamental features", the recognition was performed using a backpropagation neural network.
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