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Computational Reconstructions of Extracellular Action Potentials and Local Field Potentials of a Rat Cerebellum Using Point Neurons Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Iris Recognition Using Integer Wavelet Transform and Log Energy Entropy

Authors : Jincy J. Fernandez, Nithyanandam Pandian

Published in: Advances in Computing and Network Communications

Publisher: Springer Singapore

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Abstract

As the technology is reaching its next level day by day, the concerns over information or data security are also creeping up. Biometric systems have been widely used in many real-world applications in order to provide more security to the data. Iris recognition system has become a widely used system for human identification from the last few decades. In this paper, an efficient iris recognition system is proposed where iris localization is carried out by first finding the pupil-iris boundary using the connected component analysis approach. And then by considering the pupil center as the reference point, it traverses through the virtual outer boundary to detect the iris-sclera boundary. After applying normalization on the iris region, the iris region is partitioned into non-overlapping blocks. Further, a combination of integer wavelet transform (IWT) with log energy entropy (LEE) is applied on each block to extract the unique iris code as the feature vector. The experiments have been conducted using the multimodal biometric database, SDUMLA-HMT. The proposed system has succeeded in achieving a low false acceptance rate and a very low false rejection rate. Also, the uniqueness of the iris patterns is evaluated in terms of degrees of freedom and is found to be a promising one.

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Metadata
Title
Iris Recognition Using Integer Wavelet Transform and Log Energy Entropy
Authors
Jincy J. Fernandez
Nithyanandam Pandian
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Computing and Network Communications

Print ISBN: 978-981-336-986-3

Electronic ISBN: 978-981-336-987-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-33-6987-0_2