使用该B-P神经网络作为汉字的分类器，可以大大提高车牌汉字的识别率。

These features are used to train a B-P neural network, it is a classifier and can improve greatly the recognition rate of Chinese characters.

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由于车牌汉字往往存在笔画断裂或粘连、字迹模糊、字形倾斜等问题，导致难以采用常规的方法对其进行识别。

For the reason that it's difficult to recognize license plate Chinese characters through a conventional method because of conjoint or broken strokes, illegible writing and inclined font.

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传统的车牌汉字的特征提取方法是在具有先验知识的情况下进行的，先验知识的好坏对结果有着非常重要的影响。

Presently traditional method of car plate Chinese character feature extraction is based on prior knowledge which is important for the result.

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