Open AccessFingerprint frequency normalisation and enhancement using two‐dimensional short‐time Fourier transform analysis
Author(s) -
Ghafoor Mubeen,
Taj Imtiaz Ahmad,
Jafri Mohammad Noman
Publication year - 2016
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2016.0005
Subject(s) - fingerprint (computing) , distortion (music) , frequency domain , artificial intelligence , computer science , fourier transform , short time fourier transform , ridge , computer vision , spatial frequency , gaussian , spatial filter , fingerprint recognition , pattern recognition (psychology) , mathematics , fourier analysis , optics , telecommunications , physics , amplifier , mathematical analysis , paleontology , bandwidth (computing) , quantum mechanics , biology
A fingerprint image with non‐uniform ridge frequencies can be considered as a two‐dimensional dynamic signal. A non‐uniform stress on the sensing area applied during fingerprint acquisition may result in a non‐linear distortion that disturbs the local frequency of ridges adversely affecting the matching performance. This study presents a new approach based on Short time Fourier transform analysis and local adaptive contextual filtering for frequency distortion removal and enhancement. In the proposed approach, the fingerprint image is divided into sub‐images to determine local dominant frequency and orientation. Gaussian Directional band pass filtering is then adaptively applied in frequency domain. These filtered sub‐images are then combined in spatial domain using a novel technique to obtain the enhanced fingerprint image of high ridge quality and uniform inter‐ridge distance. Simulation results show the efficacy of the proposed enhancement technique as compared to other well‐known contextual filtering based enhancement techniques reported in the literature.