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Application of Fractal Theory for On-Line and Off-Line Farsi Digit Recognition

机译:分形理论在在线和离线波斯数字识别中的应用

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摘要

Fractal theory has been used for computer graphics, image compression and different fields of pattern recognition. In this paper, a fractal based method for recognition of both on-line and off-line Farsi/ Arabic handwritten digits is proposed. Our main goal is to verify whether fractal theory is able to capture discriminatory information from digits for pattern recognition task. Digit classification problem (on-line and offline) deals with patterns which do not have complex structure. So, a general purpose fractal coder, introduced for image compression, is simplified to be utilized for this application. In order to do that, during the coding process, contrast and luminosity information of each point in the input pattern are ignored. Therefore, this approach can deal with on-line data and binary images of handwritten Farsi digits. In fact, our system represents the shape of the input pattern by searching for a set of geometrical relationship between parts of it. Some fractal-based features are directly extracted by the fractal coder. We show that the resulting features have invariant properties which can be used for object recognition.
机译:分形理论已被用于计算机图形学,图像压缩和模式识别的不同领域。本文提出了一种基于分形的在线和离线波斯/阿拉伯手写数字识别方法。我们的主要目标是验证分形理论是否能够从数字中捕获区分性信息以进行模式识别。数字分类问题(在线和离线)处理的是没有复杂结构的模式。因此,引入用于图像压缩的通用分形编码器被简化以用于该应用。为此,在编码过程中,输入模式中每个点的对比度和亮度信息被忽略。因此,这种方法可以处理在线数据和手写波斯数字的二进制图像。实际上,我们的系统通过搜索输入部分之间的一组几何关系来表示输入模式的形状。分形编码器直接提取一些基于分形的特征。我们证明了生成的特征具有可用于对象识别的不变属性。

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