使用卷积神经网络识别印尼身份证

M. O. Pratama, W. Satyawan, Bagus Fajar, Rusnandi Fikri, Haris Hamzah
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引用次数: 9

摘要

印尼身份证可用于识别印尼公民身份的几个要求,如销售和采购记录,入场和其他交易处理系统(TPS)。目前的TPS系统采用手工输入市民身份证数据的方式,耗时长,容易出错,效率低。在这项研究中,我们提出了一个使用最先进的深度学习模型:卷积神经网络(CNN)的公民身份证检测模型。结果表明,利用深度学习技术可以获得正准确率的公民身份证识别。我们还将CNN的结果与传统的计算机视觉技术进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indonesian ID Card Recognition using Convolutional Neural Networks
Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques.
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