Jaafar, Haryati and Ibrahim, Salwani and Ramli, Dzati Athiar
(2015)
A Robust and Fast Computation Touchless Palm Print
Recognition System Using LHEAT and the IFkNCN Classifier.
Computational Intelligence and Neuroscience, 2015 (360217).
pp. 1-17.
ISSN 1687-5265
Abstract
Mobile implementation is a current trend in biometric design.This paper proposes a new approach to palm print recognition, in
which smart phones are used to capture palm print images at a distance.Atouchless systemwas developed because of public demand
for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for
effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extractionmethod
were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding
or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the
recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN), was implemented. By removing
outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate
that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%.
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