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Research of ID Card Recognition Algorithm Based on Neural Network Pattern Recognition

机译:基于神经网络模式识别的ID卡识别算法研究

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How to quickly and correctly identify the second generation ID card code has important practical significance in real life. The algorithms have been presented about the recognition and verification code of ID cards. In order to let computer own the knowledge of code of character image, firstly, transform the image of ID cards to binary image, then segment image character of ID card code and display image character using image processing technique, secondly manual input corresponding correct code of character image, thirdly character image is classification stored in the corresponding folder according to the corresponding correct code. These character images are training samples, which are trained using the matlab toolbox of the neural network pattern to generate training model. Using the generated the training model to identify code of the ID cards. The validation algorithm is based on the generated the training model to identify code of ID cards. Compare the consistent of code of ID cards to identify the code, if recognition accuracy rate is not high, the training model need to be trained again, until the recognition accuracy rate is more than 95%. Neural network pattern recognition and verification algorithm can take advantage of the training model to perfectly realize identification and validation the code of the second-generation ID card, the algorithms have application value in the real work.
机译:如何快速正确地识别第二代ID卡代码在现实生活中具有重要的实际意义。已经介绍了算法关于ID卡的识别和验证码。为了让计算机拥有字符图像代码的知识,首先,将ID卡的图像转换为二进制图像,然后使用图像处理技术的ID卡代码和显示图像字符的段图像字符,其次是手动输入相应的正确代码字符图像,第三字符图像是根据相应的正确代码存储在相应文件夹中的分类。这些字符图像是训练样本,其使用神经网络模式的MATLAB工具箱进行培训以生成训练模型。使用生成的训练模型来识别ID卡的代码。验证算法基于生成的训练模型来识别ID卡代码。比较ID卡代码的一致性来识别代码,如果识别精度率不高,则需要再次培训训练模型,直到识别精度率超过95%。神经网络模式识别和验证算法可以利用训练模型来完美地实现识别和验证第二代ID卡的代码,算法在真实工作中具有应用价值。

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