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Part of book or chapter of book
License: CC BY
Data sources: UnpayWall
https://doi.org/10.5772/17089...
Part of book or chapter of book . 2011 . Peer-reviewed
Data sources: Crossref
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Solutions for Iris Segmentation

Authors: Milena Bueno Pereira Carneiro; Antonio Claudio P. Veiga; Edna Lucia; Gilberto A.;

Solutions for Iris Segmentation

Abstract

The growing concern with security and access control to places and sensitive information has contributed for the increased utilization of biometric systems. Biometry is the name given to the techniques used to recognize people automatically through physical and behavioural characteristics of the human body such as those found on the face, fingerprint, hand geometry, iris, signature or voice. From all the biometric options, iris recognition deserves special attention as the iris contains a huge and unique richness of characteristics, which do not change over time and enables the construction of extremely reliable and accurate systems. The iris recognition process is relatively complex and involves several stages of processing as illustrated in Figure 1. The first stage corresponds to the localization of the region of the iris on the image of the eye, which also involves the extraction of the regions corrupted by the superior and inferior eyelids and eyelashes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
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Green