2025/04/18 by Josep De Alcaraz‐Fossoul, Michelle V. Mancenido, Jena Aileen Johanson +1 · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · Social Sciences · #Biometric Identification and Security #Forensic Fingerprint Detection Methods #Forensic and Genetic Research
paper · pdf · doi:10.1111/1556-4029.70055
openalex publication_date 2025/04/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
In this article, a redefined gage reproducibility and repeatability (R&R) method is proposed to identify possible sources of error and variation components in a fingerprint morphometric measurement system. Unlike traditional gage R&R, this new method incorporates a linear mixed effects model that accounts for a mix of random and fixed effects, nested factors, and repeated measurements. The model relies on the analysis of data from one study involving the measurement of ridge width dimensions. The data set was collected from four types of finger impressions provided by 10 donors: inked-rolled (RL) and inked-flat (FL) on paper, as well as minimally distorted latents recovered with white powder (LW) and black powder (LB) on plastic. To assess reproducibility and repeatability, four examiners manually measured each impression 24-36 times at predetermined ridge locations, generating ≈3000-4000 measurements per appraiser. The results highlight the effect of minimal skin distortion on ridge width measurements and reveal high repeatability (i.e., low intra-examiner variation) but relatively low reproducibility among examiners (i.e., high inter-examiner variation). Further, it is demonstrated that the variance decomposition framework is effective in parsing out sources of variation in the ridge width measurement process.