Dermatoglyphic Analysis On The Morphology Of Pores And Its Importance In Forensic Investigation

Abstract

Latent fingerprint analysis remains pivotal for forensic investigation in identifying an individual and in criminal profiling. This research investigates the efficiency of Ridgeology and poroscopy, the analysis of the ridge characteristics, and the sweat pores quantitatively as an extension of the Optimal Score Assigned (OSA) framework proposed by Gnanasivam, P., & Vijayarajan, R. (2019). The samples were collected using a stratified method, cohorts (n=500) by age group (C1 to C5), ranging from 15 to 65, and the sexes with a 1:1 ratio. High-fidelity frictional ridge images were acquired using a digital microscope, and studies were conducted using the Proscope software.Ridge count (RC) and fingertip size (FTS) were quantified and found to be efficient in sex determination. However, it was not effective to determine the age of the fingerprint donor. This research focused on the given fragmentary nature of latent prints at crime scenes. Considering the practical application of the OSA method to the crime scene samples, the hypothesis was tested on the ridge thickness (RT) and pore density (PD) along with the traditional ridge density (RD) and the fingertip size (FTS) parameters. The statistical model yielded the gender classification with 88.41% accuracy with RD and FTS factors. However, RT and PD showed a significant difference between the inter-category and intra-category with respect to the age of the fingerprint donor. Identifying value distribution across the PD/RT-modified OSD formula confirmed the metrics’ forensic reliability and augmented a classification precision under latent print constraints. This study highlights the importance of the integration of poroscopy into the OSA Model as a methodology for estimating the age of the fingerprint donor, aiding in forensic investigation, personal identification, and criminal profiling.