Minutia cylinder code-based fingerprint matching optimization using GPU

Muhamad Visat Sutarno, A. I. Kistijantoro
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引用次数: 3

Abstract

The advancement of technology has been giving contributions to the rapid growth of the use of digital data. In this digital era, lots of physical data have been transformed into the digital ones. One example of the use of digital data is the digital biometric fingerprint data on the Electronic Identity Card (KTP-el). Fingerprint matching can take a long time to process if the data is large enough. Thus, there is a need for a parallel fingerprint matching. Based on this rationale, this paper aims to improve the fingerprint matching performance, in the current state of the art linear solution, by using the Minutia Cylinder-Code (MCC) algorithm in parallel on GPU. Based on the experiment and testing, the proposed solution has a significantly better run time compared to the state of the art linear solution while maintaining the accuracy.
基于精细圆柱代码的指纹匹配GPU优化
技术的进步促进了数字数据使用的快速增长。在这个数字时代,大量的物理数据已经转化为数字数据。使用数字数据的一个例子是电子身份证(KTP-el)上的数字生物特征指纹数据。如果数据足够大,指纹匹配可能需要很长时间来处理。因此,有必要进行并行指纹匹配。基于此,本文旨在通过在GPU上并行使用Minutia圆柱体代码(MCC)算法,在当前最先进的线性解决方案中提高指纹匹配性能。根据实验和测试,与最先进的线性解决方案相比,所提出的解决方案在保持准确性的同时具有更好的运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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