使用虹膜和生物识别技术进行银行交易

Shruthi C.K., Balaji M, Arjun Sathish B.K, Dinesh S
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引用次数: 0

摘要

非接触式二维独特指纹图像与接触式指纹的精确相关性是开发非接触式二维独特指纹创新技术的基础,这种创新技术可提供更无菌、无失真的独特指纹特征。卷积神经系统(CNN)已在生物识别中展示了其强大的能力。尽管如此,利用基于 CNN 的方法来协调独特标记图片的尝试几乎为零。本文建立了一个基于 CNN 的系统,以精确协调非接触式和接触式独特标记图片。我们的结构一开始就利用独特的手指印记细节、单独的边缘导向和边缘轮廓的特定区域准备了一个多暹罗 CNN。关键字:生物识别、样本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BANK TRANSACTION USING IRIS AND BIOMETRIC
Exact correlation of contactless 2D unique finger impression pictures with contact-based fingerprints is basic for the achievement of developing contactless 2D unique finger impression innovations, which offer more sterile and distortion free procurement of unique finger impression features. Convolutional neural systems (CNN) have demonstrated comment capable capacities in biometrics acknowledgment. Be that as it may, there has been nearly nil endeavor to coordinate unique mark pictures utilizing CNN- based methodologies. This paper builds up a CNN- based system to precisely coordinate contactless and contact-based unique mark pictures. Our structure right off the bat prepares a multi-Siamese CNN utilizing unique finger impression details, individual edge guide and particular district of edge outline. Key Words: Biometric, samples.
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