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Comparitive Analysis of Conventional, Real and Complex Wavelet Transforms for Iris Recognition

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IJCA Proceedings on International Conference on Internet of Things, Next Generation Networks and Cloud Computing
© 2016 by IJCA Journal
ICINC 2016 - Number 2
Year of Publication: 2016
Authors:
Mansa S. Mane
Sunil M. Sangve

Mansa S Mane and Sunil M Sangve. Article: Comparitive Analysis of Conventional, Real and Complex Wavelet Transforms for Iris Recognition. IJCA Proceedings on International Conference on Internet of Things, Next Generation Networks and Cloud Computing ICINC 2016(2):14-17, July 2016. Full text available. BibTeX

@article{key:article,
	author = {Mansa S. Mane and Sunil M. Sangve},
	title = {Article: Comparitive Analysis of Conventional, Real and Complex Wavelet Transforms for Iris Recognition},
	journal = {IJCA Proceedings on International Conference on Internet of Things, Next Generation Networks and Cloud Computing},
	year = {2016},
	volume = {ICINC 2016},
	number = {2},
	pages = {14-17},
	month = {July},
	note = {Full text available}
}

Abstract

Iris Recognition System is a process of recognizingan individual by analyzing the random pattern of iris and comparing with database. In this paper comparative analysis is perform with wavelet transform such as 2D Discrete wavelet transform (2D-DWT), Real dual tree Discrete wavelet transform (R-DT-DWT) and Complex dual tree Discrete wavelet transform (C-DT-DWT) for iris recognition. These approaches are tested on various databases. The process starts from pre-processing. In pre-processing stage the image is enhanced, segmented and normalized. Now smoothed image is taken into consideration for feature extraction using above mentioned wavelet transforms. Finally image is applied post-classifier for reducing false rejection rate.

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