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Id Card Number Identification Based on Artificial Neural Network

机译:基于人工神经网络的ID卡号识别

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His article to include Arabic Numbers, photographs, and a number of special symbol scanning character image as the object of identification, on the key technology of the id card number character recognition research, analyzes various factors that influence efficiency of identification, the effectiveness of the various modules in the process of character recognition algorithm are key research and elaborate in detail, finally complete the character recognition system based on improving the algorithm design, implementation and testing. The main tasks include the following: First, detailed several image the binarization processing methods, compare the treatment effect. Uneven distribution of the target area and the background area, difficult to isolate the problem, proposed and implemented improvements based on local iterative Otsu algorithm to verify its validity by experiment. Second, brief introduction to the feature extraction methods for character recognition. Back-propagation neural network research on the application of a wide range of error, the overall adaptive momentum term and the learning rate for BP network slow network convergence, easy to fall into local minimum defects such improvements, improved classifier and experimental verification of its superiority. Third, complete the entire character recognition system design, implementation, and testing. The actual test results show that: The proposed algorithm, and design of the system is feasible and effective, while the entire system algorithm is able to meet the requirements of quick identification.
机译:他的文章包括阿拉伯数字,照片和许多特殊符号扫描字符图像作为识别对象,在身份证号码字符识别研究的关键技术上,分析了影响识别效率的各种因素,效果在字符识别算法过程中的各种模块是关键的研究和详细详细设计,最后完成了基于改进算法设计,实现和测试的字符识别系统。主要任务包括以下内容:首先,详细的几个图像二值化处理方法,比较治疗效果。目标区域和背景区域的分布不均匀,难以隔离问题,基于局部迭代OTSU算法来识别和实现改进,通过实验验证其有效性。其次,简要介绍了字符识别的特征提取方法。背部传播神经网络研究对广泛误差的应用,整体自适应动量术语和BP网络的学习率慢网络收敛,易于陷入局部最小缺陷此类改进,改进分类器和实验验证其优越性的实验验证。三,完成整个字符识别系统设计,实现和测试。实际测试结果表明:建议的算法和系统的设计是可行且有效的,而整个系统算法能够满足快速识别的要求。

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