探索指纹模式和脊数在传记体关联中的应用

Dale Herdegen, M. Loew
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引用次数: 2

摘要

指纹特征描述人和群体。一个人可以通过指纹图案和脊数进行近似描述,并通过指纹细节进行唯一描述。一个组可以用总体模式频率和平均脊数(每个人或每个手指)来描述。当一个群体由相关的人组成时,指纹的遗传基础在该群体内产生共同的定性和定量指纹特征。这些共同特征使得内婚制(通过婚姻联系)群体之间存在差异;法医人类学中有很多例子,详细说明了基于种族、宗教、地理或种姓的内婚群体之间皮肤刻字的差异。本文考察了离散内婚制群体之间的分化程度,并通过比较个体与群体的指纹特征,探讨了将个体与群体联系起来的能力。此处引用的皮肤纹人类学研究数据用于说明基于指纹模式和/或脊数区分群体的能力。在某些情况下,群体之间的分化程度表明,有可能确定个体与群体的联系。本文提出了一个案例研究,通过比较个体每指模式和脊数与组合群体模式和脊数信息,说明了一个人与两个内婚群体之一的关联。在这种情况下,使用决策树分类器实现了大约80%的关联准确性。在这个有限的案例中取得的成功表明进一步研究使用指纹特征将人与群体联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the uses of fingerprint patterns and ridge-counts in biographical associations
Fingerprint characteristics describe people and groups. A person can be described approximately by fingerprint patterns and ridge-counts, and described uniquely by fingerprint minutiae. A group can be described by overall pattern frequencies and average ridge-counts (per-person or per-finger). When a group comprises related persons, the genetic basis of fingerprints produces common qualitative and quantitative fingerprint characteristics within the group. Those common characteristics allow for differentiation between endogamous (related by marriage) groups; forensic anthropology is replete with examples detailing the dermatoglyphic differences between endogamous groups based on race, religion, geography, or caste. This paper examines the degree of differentiation between discrete endogamous groups and explores the ability to associate an individual to a group by comparing individual-to-group fingerprint characteristics. Data from dermatoglyphic anthropologic studies cited herein are used to illustrate the ability to differentiate groups based on fingerprint pattern and/or ridge-counts. In some instances, the degree of differentiation between groups suggests that it is possible to identify associations of individuals to a group. A case study is presented that illustrates the association of a person to one of two endogamous groups by comparing individual per-finger patterns and ridge-counts to composited group pattern and ridge-count information. In this case, approximately 80 percent association accuracy was achieved using a decision tree classifier. The success achieved in this limited case suggests further study in associating persons to groups using fingerprint characteristics.
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