Are human faces unique? A metric approach to finding single individuals without duplicates in large samples. (December 2015)

• Record Type: Journal Article
• Authors: Lucas, Teghan; Henneberg, Maciej
• Is Part Of: Forensic science international. Volume 257(2015)
• Page Start: 514.e1
• Page End: 514.e6
• Publication Date: 2015-12
• Subjects: Forensics -- Human variation -- Identification -- Singularity -- Forensic anthropology population data; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2015.09.003
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Uniqueness is a doubtful concept in the forensic sciences as it cannot be proven. A new concept 'singularity in a defined sample' overcomes the problems associated with uniqueness. The way to achieve singularity is illustrated using a sample of anthropometric measurements (ANSUR). With 8 metric traits no two matching individuals can be found among 3982 persons. Number of traits required to achieve singularity increases with sample size. Abstract: In the forensic sciences it is inferred that human individuals are unique and thus can be reliably identified. The concept of individual uniqueness is claimed to be unprovable because another individual of same characteristics may exist if population size were infinite. It is proposed to replace "unique" with "singular" defined as a situation when only one individual in a specific population has a particular set of characteristics. The likelihood that in a population there will be no duplicate individual with exactly the same set of characteristics can be calculated from datasets of relevant characteristics. To explore singularity, the ANSUR database which contains anthropometric measurements of 3982 individuals was used. Eight facial metric traits were used to search for duplicates. With the addition of each trait, the chances of finding a duplicate were reduced until singularity was achieved. Singularity was consistently achieved at a combination of the maximum of seven traits. The larger the traits in dimension, the faster singularity was achieved. By exploring how singularity is achieved in subsamples of 200, 500, etc. it has been determined that about one trait needs to be added when the size of the target population increases by 1000 individuals. With the combination of four facial dimensions, it is possible to achieve a probability of finding a duplicate of the order of 10 −7, while, the combination of 8 traits reduces probability to the order of 10 −14, that is less than one in a trillion.