Objective: This research aimed to test the reproducibility and applicability of the human identification method using photographs of the ears proposed by Cameriere et al. in a Brazilian sample. Materials and Methods: Photographs of both ears of 115 participants were captured and evaluated by three different examiners. The data obtained were submitted to Kendall's Agreement Coefficient to assess interobserver agreement, in addition to descriptive statistics to assess the proportions of the areas of each ear. The Wilcoxon test was applied to determine the similarity of the proportions of the ear. To test the ability to identify a person based on the parameters of the ear, the k-dimensional tree algorithm was used. Results: There was a high interobserver agreement, and the size and proportions obtained between the ears were similar, except for helix proportion. Thus, most of the parameters of an ear can be identified based on the parameters of the opposite ear, and that the parameters associated with the algorithm used can classify and group a set of ears based on the similarity of their measurements. Conclusion: It can be concluded that the method proved to be reproducible and useful as a method of human identification in a Brazilian sample.

Human identification by the ear: Reproducibility and applicability in a Brazilian sample

Cameriere R.;
2021-01-01

Abstract

Objective: This research aimed to test the reproducibility and applicability of the human identification method using photographs of the ears proposed by Cameriere et al. in a Brazilian sample. Materials and Methods: Photographs of both ears of 115 participants were captured and evaluated by three different examiners. The data obtained were submitted to Kendall's Agreement Coefficient to assess interobserver agreement, in addition to descriptive statistics to assess the proportions of the areas of each ear. The Wilcoxon test was applied to determine the similarity of the proportions of the ear. To test the ability to identify a person based on the parameters of the ear, the k-dimensional tree algorithm was used. Results: There was a high interobserver agreement, and the size and proportions obtained between the ears were similar, except for helix proportion. Thus, most of the parameters of an ear can be identified based on the parameters of the opposite ear, and that the parameters associated with the algorithm used can classify and group a set of ears based on the similarity of their measurements. Conclusion: It can be concluded that the method proved to be reproducible and useful as a method of human identification in a Brazilian sample.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/130396
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