Fingerprint, as one of the most popular and robust biometric traits, can be used in automatic identification and verification systems to identify individuals. Fingerprint matching is a vital and challenging issue in fingerprint recognition systems. Most fingerprint matching algorithms are minutiae-based. The minutiae in fingerprints can be determined by their discontinuity. Ridge ending and ridge bifurcation are two frequently used minutiae in most fingerprint-based matching algorithms. This paper presents a new minutiae-based fingerprint matching using the onion peeling approach. In the proposed method, fingerprints are aligned to find the matched minutiae points. Then, the nested convex polygons of matched minutiae points are constructed and the comparison between peer-to-peer polygons is performed by the turning function distance. Simplicity, accuracy, and low time complexity of the Onion peeling approach are three important factors that make it a standard method for fingerprint matching purposes. The performance of the proposed algorithm is evaluated on the database $FVC2002$. The results show that fingerprints of the same fingers have higher scores than different fingers. Since the fingerprints that the difference between the number of their layers is more than $2$ and the minutiae matching score lower than 0.15 are ignored, the better results are obtained.

翻译：作为最受欢迎和最有力的生物鉴别特征之一,指纹可以用于自动识别和核查系统,以识别个人。指纹匹配是指纹识别系统中一个重要和具有挑战性的问题。大多数指纹匹配算法都是基于细小的。指纹匹配算法的细小部分可以由不连续来决定。在大多数基于指纹的匹配算法中,脊尾和脊脊两侧是两种经常使用的细小部分。本文展示了一种使用洋葱剥皮方法的基于细小的指纹匹配。在拟议方法中,指纹与匹配的细小点匹配。然后,搭建了匹配点的嵌套式锥形圆形多边形,对等对等多方形的比较可以通过旋转功能距离来进行。在大多数基于指纹的匹配算法中,斜度、精度和低时间复杂性是三个重要因素,使得它成为指纹匹配目的的标准方法。在数据库中,对拟议算法的性进行了评估。结果显示,同一手指的指纹的分数高于相近点的分数,而其分数的分数则低于0.25的分。因此,比其分数的比分数的分数要低。