Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6574
Title: Optimal wavelength band clustering for multispectral iris recognition
Authors: Gong, Y
Zhang, DD 
Shi, P
Yan, J
Keywords: Biometrics
Principal component analysis
Issue Date: 1-Jul-2012
Publisher: Optical Society of America
Source: Applied optics, 1 July 2012, v. 51, no. 19, p. 4275-4284 How to cite?
Journal: Applied optics 
Abstract: This work explores the possibility of clustering spectral wavelengths based on the maximumdissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.
URI: http://hdl.handle.net/10397/6574
ISSN: 1559-128X
EISSN: 2155-3165
DOI: 10.1364/AO.51.004275
Rights: © 2012 Optical Society of America. This paper was published in Applied Optics and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-51-19-4275. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
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