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A Method for Genetic Selection of the Most Characteristic Descriptors of the Dynamic Signature

机译:动态签名最特征描述符的遗传选择方法

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摘要

Dynamic signature verification is an important area of biometrics. In this area methods from the field of computational intelligence can be used. In this paper we propose a new method for genetic selection of the most characteristic descriptors of the dynamic signature. The descriptors are global features of the signature and components created within its partitions. Selection of the descriptors is realized individually for each user of the biometric system. Its purpose is to increase the precision of the biometric system by eliminating the descriptors which do not increase efficiency of verification procedure. Number of descriptors (their combination) can be high, so the use of genetic algorithm to reduce their number seems to be justified. Moreover, reduction of descriptors increases interpretability of fuzzy mechanism for evaluation of signatures' similarity. Proposed method was tested using known dynamic signatures database-MCYT-100.
机译:动态签名验证是生物识别技术的重要领域。在这一领域中,可以使用来自计算智能领域的方法。在本文中,我们提出了一种用于动态签名最特征描述子遗传选择的新方法。描述符是签名和在其分区内创建的组件的全局功能。描述符的选择是针对生物识别系统的每个用户单独实现的。其目的是通过消除不增加验证程序效率的描述符来提高生物识别系统的精度。描述符(它们的组合)的数量可能很高,因此使用遗传算法减少其数量似乎是合理的。此外,减少描述符可以增加模糊机制的可解释性,以评估签名的相似性。使用已知的动态签名数据库-MCYT-100对提出的方法进行了测试。

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