Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength

Authors:
Hugo Proenca
Affiliations:
Universidad da Beira Interior, Covilhã
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2010

Citing 0
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Fusing color and shape descriptors in the recognition of degraded iris images acquired at visible wavelengths

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Multispectral scleral patterns for ocular biometric recognition

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Effective elliptic fitting for iris normalization

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Abstract

Iris recognition imaging constraints are receiving increasing attention. There are several proposals to develop systems that operate in the visible wavelength and in less constrained environments. These imaging conditions engender acquired noisy artifacts that lead to severely degraded images, making iris segmentation a major issue. Having observed that existing iris segmentation methods tend to fail in these challenging conditions, we present a segmentation method that can handle degraded images acquired in less constrained conditions. We offer the following contributions: 1) to consider the sclera the most easily distinguishable part of the eye in degraded images, 2) to propose a new type of feature that measures the proportion of sclera in each direction and is fundamental in segmenting the iris, and 3) to run the entire procedure in deterministically linear time in respect to the size of the image, making the procedure suitable for real-time applications.