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Study of VIN Based on BP Neural Network Recognition

机译:基于BP神经网络识别的VIN研究。

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摘要

A new fuzzy recognition method of machine-printed VIN number based on neural network is presented. This method includes ten links: VIN number detection and separation of right on top of VIN, binarization, denoising, incline correction, extraction of VIN numerals, window scaling, location standardization, thinning, extraction of numeral feature and fuzzy recognition based on BP neural network. Through testing, the recognition rate of this method can be over 95 %. The recognition time of characters for character is less than 1 s, which means that the method is of more effective recognition ability and can better satisfy the real system requirements.
机译:提出了一种基于神经网络的机印VIN号模糊识别新方法。该方法包括十个环节:VIN数检测和VIN右上角的分离,二值化,去噪,倾斜校正,VIN数的提取,窗口缩放,位置标准化,细化,数字特征的提取以及基于BP神经网络的模糊识别。 。经过测试,该方法的识别率可以达到95%以上。字符对字符的识别时间小于1 s,这意味着该方法具有更有效的识别能力,可以更好地满足实际系统的要求。

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