Fingerprint Sub-Classification and Singular Point Detection

Abstract

This paper presents a novel approach to fingerprint singular point detection. Singular points (cores and deltas) are used for fingerprint classification, sub-classification and registration. This method exploits the stability of the directional field pattern extracted from singular point regions at different resolution levels. The procedure is invariant to translations, scaling and small rotations. A fingerprint sub-classification procedure was built based on the proposed singular point detection method. Two kinds of tests were conducted on a subset consisting of 955 NIST-14 fingerprint images. First, automatic and forensic expert sub-classifications were compared. Second, the consistency of the proposed method was measured comparing automatic sub-classification for two different rolls of the same fingerprint.