Abstract
Background: Biometric technologies for human identification have recently gained much attention. Because of their unique features of absolute identity and their frequent presence at crime scenes, fingerprints of an individual are considered one of the most important identification tools. The current work aims to study the usage of fingerprint ridge density for age and sex identification Methods: Fingerprint ridge density was investigated in 233 healthy Egyptian volunteers (130 males and 103 females), aged between 4 and 86 years, and was calculated as the number of ridges in 25 mm2 areas. Linear regression was applied for age identification and Discriminant function analysis & Roc curve were done for sex identification. Results: There is decreasing in ridge density with aging, and we were able to obtain eight novel equations to determine the age for each individual fingerprint density. Ten novel equations to determine sex were obtained for each individual fingerprint density. In addition, we were able to gain two novel cut-off values by the Roc curve for sex identification. Conclusion: Age and sex differentiation can be applicable based on fingerprint ridge density using linear regression analysis, discriminant function analysis, and Roc curve methods; hence it is recommended to be employed in forensic practice.