Multispectral Ocular Biometrics

Crihalmeanu, Simona; Ross, Arun

doi:10.1007/978-3-319-28501-6_15

Cited by 4 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unfortunately, this may not give an accurate indication about the iris performance as the images do not belong to the same subject. In [22], the authors suggested enhancing iris recognition performance in non-frontal images through multi-spectral fusion of iris pattern and scleral texture. Since the scleral texture is better seen in VL and the iris pattern is observed in NIR, multi-spectral fusion could improve the overall performance.…”

Section: Related Workmentioning

confidence: 99%

A novel framework for cross-spectral iris matching

Abdullah

Dlay

Woo

et al. 2016

IPSJ T Comput Vis Appl

View full text Add to dashboard Cite

Previous work on iris recognition focused on either visible light (VL), near-infrared (NIR) imaging, or their fusion. However, limited numbers of works have investigated cross-spectral matching or compared the iris biometric performance under both VL and NIR spectrum using unregistered iris images taken from the same subject. To the best of our knowledge, this is the first work that proposes a framework for cross-spectral iris matching using unregistered iris images. To this end, three descriptors are proposed namely, Gabor-difference of Gaussian (G-DoG), Gabor-binarized statistical image feature (G-BSIF), and Gabor-multi-scale Weberface (G-MSW) to achieve robust cross-spectral iris matching. In addition, we explore the differences in iris recognition performance across the VL and NIR spectra. The experiments are carried out on the UTIRIS database which contains iris images acquired with both VL and NIR spectra for the same subject. Experimental and comparison results demonstrate that the proposed framework achieves state-of-the-art cross-spectral matching. In addition, the results indicate that the VL and NIR images provide complementary features for the iris pattern and their fusion improves notably the recognition performance.

show abstract

Section: Related Workmentioning

confidence: 99%