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English Character Recognition Based on Feature combination

机译:基于特征组合的英文字符识别

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摘要

In order to solve the polluted English character recognition problem with interference of external noise, a new approach based on feature combination and BP network is presented in this paper.By extracting the structural features and the statistical features from the English characters, respectively, the approach can include more classify information.Subsequently, two kinds of features are normalized and further are combined.For illustration, the combined features are sent to the classifier such as BP network, which is utilized to show the feasibility of the new approach in solving the interference of external noise and accomplish the recognition.Experimental results show that the convergent performance of BP network trained by the combined features is only within 184 epochs while compared with that of BP network trained by the other feature vectors. The method based on combined features can effectively solve the interference of external noise and thus superior performance in terms of English character recognition capability can be achieved.
机译:为了解决外界噪声干扰下污染英文字符的问题,提出了一种基于特征组合和BP网络的新方法。分别从英文字符中提取结构特征和统计特征。可以将更多的分类信息归一化,然后将两种特征归一化并进一步组合,为便于说明,将组合的特征发送到分类器(例如BP网络),以证明新方法解决干扰的可行性实验结果表明,与其他特征向量训练的BP网络相比,组合特征训练的BP网络的收敛性能仅在184个纪元以内。基于组合特征的方法可以有效地解决外界噪声的干扰,从而在英文字符识别能力方面具有优越的性能。

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