一种转换生物特征的新方法——利用神经网络

E. Gopi, P. Vijayakumar, S. Pandiyan, P. Kannan, R. Perumal
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引用次数: 1

摘要

生物识别技术是利用从面部、拇指、视网膜、眼睛等处收集的独特遗传特征作为身份验证代码的技术。对一个人来说,有效的生物特征的数量是有限的。任何报名参加多个组织的人,都必须使用上述不同的生物识别信息,这样就有了防傻瓜的真实性,没有任何可能篡改一个组织的生物识别数据被另一个组织。但一个创新的想法是使用一种技术,在不同的组织中使用相同的生物识别技术。该技术必须使其难以反转(即)原始生物特征不能通过任何逆变换来恢复。提出了一种利用人工神经网络在“空间域”变换生物特征的新方法。通过该方法,可以从原始采集的生物特征数据中通过不同的变换生成不同的失真生物特征图像,从而使相同的生物特征数据可以被不同的组织使用。所提出的方法的结果非常有希望,并已被“图像变换”原理验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel approach to transformed biometrics - using ANN
Biometrics is the technique that utilizes the distinct genetic features collected from face, thumb, retina, eye etc. as an of authentication code. The number of valid biometrics is finite for a human. Any person who enrolls in multiple organizations, would have to use his/her different biometrics as mentioned above, so that there is fool proof authenticity, without any possibility of tampering of the biometric data of one organization by the other. But an innovative idea would be to use a technique that utilizes the same biometric in different organizations. The technique must be such that it is difficult to invert (i.e.) the original biometric must not be retrievable by any inverse transformations. This paper proposes a novel approach to transform a biometric feature using artificial neural network in 'spatial domain'. By this method, different distorted biometric images by using different transformations can be created from the originally collected biometric and hence the same biometric data can be used by different organizations. The results of the proposed approach are very promising and have been validated by the 'image transformation' principles.
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