Departamento de Ciencias de la Vida, Facultad de Ciencias, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain; Instituto Universitario de Investigación en Ciencias Policiales (IUICP), Universidad de Alcalá, Alcalá de Henares, Madrid, Spain.
Departamento de Ciencias de la Vida, Facultad de Ciencias, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain.
Sci Justice. 2024 Mar;64(2):216-231. doi: 10.1016/j.scijus.2024.01.005. Epub 2024 Feb 6.
The individuality and permanence of fingerprints make of them a very useful feature in the identification of individuals. There are now automated computer programmes that allow a quick comparison between a fingermark and a database. However, in order to assess the strength of evidence in fingerprint identification, complementary information on the frequencies of the different morphological features of the dermopapillary ridges is required. This idea is used in this work as a starting point to evaluate the frequencies of the parameters used in the determination of the hand and finger in a large sample of 2600 fingerprints taken from 134 male and 127 female Spanish population. Based on these fingerprints, the frequencies of different categories of the following parameters were obtained: type of pattern, slope of the apex ridge, subtype of two-delta pattern, ridge tracing, major angle, major ridge count, bisector, rotation of the central ridge, assimilation to loops and slant. Moreover, the results have shown that these characters are useful for the determination of the hand in whorls (two-delta pattern) and loops (one-delta pattern), but not for the determination of the finger. The most useful and classificatory parameter when determining the hand of origin of a two-delta fingerprint is the slope of the apex ridge, and for the one-delta pattern, knowing the location of the delta allows the correct estimation of the hand of a fingerprint in more than 93% of the cases. The data presented in this paper are novel and can be used by latent print examiners to improve the statistical basis of their decisions in reaching conclusions.
指纹的独特性和永久性使其成为个人身份识别的非常有用的特征。现在有自动化的计算机程序可以快速比较指纹和数据库之间的差异。然而，为了评估指纹识别中证据的强度，需要补充有关嵴纹的不同形态特征的频率的互补信息。在这项工作中，我们将这个想法作为一个起点，以评估在从 134 名男性和 127 名女性西班牙人群中采集的 2600 个指纹的大样本中用于确定手和手指的参数的频率。基于这些指纹，获得了以下参数的不同类别频率：模式类型、顶点嵴斜率、双三角洲模式亚型、脊线追踪、主角度、主脊计数、平分线、中央嵴旋转、向环纹和斜纹的同化。此外，结果表明，这些特征可用于确定涡纹（双三角洲模式）和环纹（单三角洲模式）的手，但不能用于确定手指。确定双三角洲指纹起源手时最有用和分类的参数是顶点嵴的斜率，而对于单三角洲模式，了解三角洲的位置可以在超过 93%的情况下正确估计指纹的手。本文介绍的这些数据是新颖的，可由潜在指纹鉴定人员用于改进其在得出结论时的决策的统计基础。
