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Comparison of effective hough transform-based fingerprint alignment approaches

机译:基于有效霍夫变换的指纹比对方法的比较

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In this paper, two effective and mostly used Hough Transform (HT) based fingerprint alignment approaches are compared, namely; Local Match Based Alignment (LMBA) and Discretized Rotation Based Alignment (DRBA). The comparison was performed by considering different conditions of minutiae points, which are rotation, translation and the number of minutiae points. In addition, this research reports the advantages of understanding the quality and relationships between the wide varieties of existing HT based fingerprint alignment methods. Minutiae points extracted from fingerprints of FVC2000 database were used on the experiments to compare these approaches. The results revealed that LMBA approach performs better than the DRBA approach on minutiae points set with larger rotation and small number of points. The DRBA approach was found to perform better with minutiae points with large amount of translation, and the computational time was less than that of LMBA approach. However, the memory usage required in DRBA is greater than memory required in LMBA.
机译:在本文中,比较了两种基于Hough变换(HT)的有效且最常用的指纹对齐方法,即:基于本地匹配的对齐方式(LMBA)和基于离散化旋转的对齐方式(DRBA)。比较是通过考虑细节点的不同条件进行的,这些条件包括旋转,平移和细节点的数量。此外,本研究报告了了解质量和现有基于HT的指纹比对方法的各种品种之间的关系的优势。实验中使用从FVC2000数据库指纹中提取的细节点来比较这些方法。结果表明,LMBA方法在旋转较大且点数少的细节点上的性能优于DRBA方法。发现DRBA方法在细节量较大且翻译量大的情况下表现更好,并且计算时间比LMBA方法少。但是,DRBA中所需的内存使用量大于LMBA中所需的内存。

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