DEIS-Università di Bologna, via Sacchi 3, Cesena (FC) 47521, Italy.
IEEE Trans Pattern Anal Mach Intell. 2011 May;33(5):1051-7. doi: 10.1109/TPAMI.2010.228.
This paper proposes a new hash-based indexing method to speed up fingerprint identification in large databases. A Locality-Sensitive Hashing (LSH) scheme has been designed relying on Minutiae Cylinder-Code (MCC), which proved to be very effective in mapping a minutiae-based representation (position/ angle only) into a set of fixed-length transformation-invariant binary vectors. A novel search algorithm has been designed thanks to the derivation of a numerical approximation for the similarity between MCC vectors. Extensive experimentations have been carried out to compare the proposed approach against 15 existing methods over all the benchmarks typically used for fingerprint indexing. In spite of the smaller set of features used (top performing methods usually combine more features), the new approach outperforms existing ones in almost all of the cases.
本文提出了一种新的基于哈希的索引方法，以加快大型数据库中的指纹识别速度。设计了一种基于 Minutiae Cylinder-Code (MCC) 的局部敏感哈希 (LSH) 方案，该方案在将基于细节的表示(仅位置/角度)映射到一组固定长度的变换不变二进制向量方面非常有效。由于对 MCC 向量之间的相似性进行了数值逼近，因此设计了一种新的搜索算法。针对所有通常用于指纹索引的基准，对所提出的方法与 15 种现有方法进行了广泛的实验比较。尽管使用的特征集较小(性能最高的方法通常结合了更多的特征)，但新方法在几乎所有情况下都优于现有方法。
