An AFIS Candidate List Centric Fingerprint Likelihood Ratio Model Based on Morphometric and Spatial Analyses (MSA)

Abstract

The use of fingerprints for identification purposes boasts worldwide adoption for a large variety of applications, from governance centric applications such as border control to personalised uses such as electronic device authentication. In addition to being an inexpensive and widely used form of biometric for authentication systems, fingerprints are also recognised as an invaluable biometric for forensic identification purposes such as law enforcement and disaster victim identification. Since the very first forensic applications, fingerprints have been utilised as one of the most commonly used form of forensic evidence worldwide. Applications of fingerprint identification are founded on the intrinsic characteristics of the friction ridge arrangement present at the fingertips, which can be generally classified at different levels or resolutions of detail (Figure 1). Generally speaking, fingerprint patterns can be described as numerous curved lines alternated as ridges and valleys that are largely regular in terms orientation and flow, with relatively few key locations being of exception (singularities). A closer examination reveals a more detail rich feature set allowing for greater discriminatory analysis. In addition, analysis of local textural detail such as ridge shape, orientation, and frequency, have been used successfully in fingerprint matching algorithms as primary features or in conjunction with other landmark-based features.