Are Haar-like Rectangular Features for Biometric Recognition Reducible?

Publikation: Forskning - peer reviewKonferenceartikel i proceeding

Abstrakt

Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features? This paper proposes total sensitivity analysis about the mean for this purpose for two different biometric traits, iris and face. Experimental results on multiple public databases show the superiority of the proposed system, using the found influential features, compared to state-of-the-art biometric recognition systems.
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Detaljer

Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features? This paper proposes total sensitivity analysis about the mean for this purpose for two different biometric traits, iris and face. Experimental results on multiple public databases show the superiority of the proposed system, using the found influential features, compared to state-of-the-art biometric recognition systems.
OriginalsprogEngelsk
TitelProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
RedaktørerJosé Ruiz-Shulcloper, Gabriella Sanniti di Baja
Vol/bind8259
Udgivelses stedSpringer Berlin Heidelberg
UdgiverSpringer Publishing Company
Publikationsdato2013
Sider334-341
ISBN (trykt)978-3-642-41826-6
ISBN (elektronisk)978-3-642-41827-3
DOI
StatusUdgivet - 2013
Begivenhed - Havana, Cuba

Konference

Konference18th Iberoamerican Congress on Pattern Recognition
LandCuba
ByHavana
Periode20/11/201323/11/2013
SerieLecture Notes in Computer Science
ISSN0302-9743

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