一种进化神经模糊方法识别在线阿拉伯笔迹

Proceedings of the Fourth International Conference on Document Analysis and Recognition Pub Date : 1997-08-18 DOI:10.1109/ICDAR.1997.619875

A. Alimi

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引用次数: 98

摘要

作者描述了一个在线识别阿拉伯草书笔迹的系统。该系统采用遗传算法选择模糊神经网络识别的最佳字符组合。在这个系统中使用的手写文字是由运动生成理论建模的。基于这一运动理论，从每个汉字中提取的特征是描述文字曲线速度方程的神经生理和生物力学参数。提出的进化方法允许识别草书笔迹的分割过程，允许重叠的笔画具有神经生理意义。

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An evolutionary neuro-fuzzy approach to recognize on-line Arabic handwriting

The author describes a system that recognizes on-line Arabic cursive handwriting. In this system, a genetic algorithm is used to select the best combination of characters recognized by a fuzzy neural network. The handwritten words used in this system are modelled by a theory of movement generation. Based on this motor theory, the features extracted from each character are the neuro-physiological and biomechanical parameters of the equation describing the curvilinear velocity of the script. The evolutionary approach proposed permits the recognition of cursive handwriting with a segmentation procedure allowing overlapped strokes having neuro-physiological meaning.

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Proceedings of the Fourth International Conference on Document Analysis and Recognition

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