Fractals everywhere
Introduction to Grey system theory
The Journal of Grey System
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Individuality of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural hidden Markov models for biometrics: Fusion of face and fingerprint
Pattern Recognition
Computers & Mathematics with Applications
Adaptive wavelet network for multiple cardiac arrhythmias recognition
Expert Systems with Applications: An International Journal
Biometric system for person recognition using gait
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Fingerprint indexing with bad quality areas
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper proposes biometric-based fractal pattern classifier for fingerprint recognition using grey relational analysis (GRA). Fingerprint patterns have arch, loop, whorl, and accidental morphologys, and embed singular points, which result in establishing fingerprint individuality. An automatic fingerprint identification system consists of three stages: image acquisition and processing, feature extraction, and pattern recognition. Fingerprint images are captured from subjects using an optical fingerprint reader (OFR). Digital image preprocessing (DIP) is used to refine out noise, enhance the image, convert to binary image, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD) from two-dimension (2D) image. Biometric characteristics are extracted as fractal patterns using Weierstrass cosine function (WCF) with different FDs. GRA performs to compare the fractal patterns among the small-scale database. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.