Abstract
This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO)-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP) and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD) from a two-dimensional (2D) image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN) as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.
Highlights
Physiological biometrics for uniquely recognizing humans include fingerprints, facial features, hand and palm geometry, deoxyribonucleic acid DNA, retina, and vein authentication
This paper proposes combining the biometric fractal pattern and particle swarm optimization PSO -based classifier for fingerprint recognition
Its techniques have become popular for biometric security systems, including the fingerprintbased security system, identity ID card, and smart-gate system
Summary
Physiological biometrics for uniquely recognizing humans include fingerprints, facial features, hand and palm geometry, deoxyribonucleic acid DNA , retina, and vein authentication. These information are permanent and unique, and distinguish individuals from one another, and are used to identify individuals in groups in home or office buildings, industrial networks, and other controlled systems 1–4. The fingerprint-based technique is widely accepted due to its easy collection, low cost, and lack of change with age. Its techniques have become popular for biometric security systems, including the fingerprintbased security system, identity ID card, and smart-gate system. The identification function authenticates users from the fingerprint alone without the smartcards, usernames, or ID numbers. The template is compared to all records within the database and the closest match
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