Indiana University-Purdue University Indianapolis (IUPUI) / Biometrics identi es/veri es a person using his/her physiological or behavioral
characteristics. It is becoming an important ally for law enforcement and homeland
security. Among all the biometric modalities, iris is tested to be the most accurate
one. However, most existing methods are not designed for non-cooperative users and
cannot work with o -angle or low quality iris images. In this thesis, we propose a
robust multi-stage feature extraction and matching approach for non-cooperative iris
recognition. We developed the SURF-like method to extract stable feature points,
used Gabor Descriptor method for local feature description, and designed the multi-
stage feature extraction and matching scheme to improve the recognition accuracy
and speed. The related experimental results show that the proposed method is very
promising. In addition, two template security enhanced schemes for the proposed non-
cooperative iris recognition are introduced. The related experimental results show
that these two schemes can e ectively realize cancelability of the enrolled biometric
templates while at the same time achieving high accuracy.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/2631 |
| Date | January 2011 |
| Creators | Yang, Kai |
| Contributors | Du, Eliza Yingzi, Chen, Yaobin, Zheng, Jiangyu, Zou, Xukai |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
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