NCJ Number
246238
Journal
Journal of Forensic Sciences Volume: 58 Issue: 6 Dated: November 2013 Pages: 1495-1502
Date Published
November 2013
Length
8 pages
Annotation
Palmprints are identified using matching of minutia points, which can be time consuming for fingerprint experts and in database searches.
Abstract
Palmprints are identified using matching of minutia points, which can be time consuming for fingerprint experts and in database searches. This article analyzes the operational characteristics of a palmar flexion crease PFC identification software tool, using a dataset of 10 replicates of 100 palms, where the user can label and match palmar line features. Results show that 100 palmprint images modified 10 times each using rotation, translation, and additive noise, mimicking some of the characteristics found in crime scene palmar marks, can be identified with a 99.2% genuine acceptance rate and 0% false acceptance rate when labeled within 3.5 mm of the PFC. Partial palmprint images can also be identified using the same method to filter the dataset prior to traditional matching, while maintaining an effective genuine acceptance rate. The work shows that identification using PFCs can improve palmprint identification through integration with existing systems, and through dedicated palmprint identification applications. Abstract published by arrangement with Wiley.