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Hybrid detection of convex curves for biometric authentication using tangents and secants

机译:使用切线和割线混合检测凸曲线以进行生物识别

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In this paper a new authentication system using Finger Knuckle Surface is examined. This introduces a personal authentication system that can simultaneously extract and exploit Finger back Knuckle surface geometrical features. Unlike, existing work on hand and finger geometrical methods which mainly concentrates of features extraction and recognition, this methods experiments with subsets of extracted feature to achieve better performance by exploiting less number of features. This is achieved by the determination of hybrid convex curves from the finger back knuckle surface. From the identified feature curves, the subset of the features like Knuckle edge points and knuckle tip points were identified. From these identified contours, geometrical structures like tangents and secants were constructed to obtain feature information in terms of angle. This method reduces critical problems that arise due to the extraction of more number of features. Also reduces the computational complexity of the feature extraction and recognition process.
机译:在本文中,研究了使用指关节表面的新认证系统。这引入了一个个人身份验证系统,该系统可以同时提取和利用手指后关节表面的几何特征。与现有的主要集中于特征提取和识别的手和手指几何方法不同,该方法对提取的特征子集进行实验,以通过利用更少的特征来实现更好的性能。这是通过确定手指后关节表面的混合凸曲线来实现的。从识别出的特征曲线中,识别出诸如指关节边缘点和指关节尖端点之类的特征子集。从这些确定的轮廓中,可以构造出诸如切线和正割线的几何结构,以获得角度方面的特征信息。此方法减少了由于提取更多数量的特征而引起的严重问题。也降低了特征提取和识别过程的计算复杂度。

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