yes / In the health care systems, a high security level is
required to protect extremely sensitive patient records. The goal
is to provide a secure access to the right records at the right time
with high patient privacy. As the most accurate biometric system,
the iris recognition can play a significant role in healthcare
applications for accurate patient identification. In this paper, the
corner stone towards building a fast and robust iris recognition
system for healthcare applications is addressed, which is known
as iris localization. Iris localization is an essential step for
efficient iris recognition systems. The presence of extraneous
features such as eyelashes, eyelids, pupil and reflection spots
make the correct iris localization challenging. In this paper, an
efficient and automatic method is presented for the inner and
outer iris boundary localization. The inner pupil boundary is
detected after eliminating specular reflections using a
combination of thresholding and morphological operations.
Then, the outer iris boundary is detected using the modified
Circular Hough transform. An efficient preprocessing procedure
is proposed to enhance the iris boundary by applying 2D
Gaussian filter and Histogram equalization processes. In
addition, the pupil’s parameters (e.g. radius and center
coordinates) are employed to reduce the search time of the
Hough transform by discarding the unnecessary edge points
within the iris region. Finally, a robust and fast eyelids detection
algorithm is developed which employs an anisotropic diffusion
filter with Radon transform to fit the upper and lower eyelids
boundaries. The performance of the proposed method is tested
on two databases: CASIA Version 1.0 and SDUMLA-HMT iris
database. The Experimental results demonstrate the efficiency of
the proposed method. Moreover, a comparative study with other
established methods is also carried out.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/16599 |
| Date | January 2015 |
| Creators | Al-Waisy, Alaa S., Qahwaji, Rami S.R., Ipson, Stanley S., Al-Fahdawi, Shumoos |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Conference paper, Accepted Manuscript |
| Rights | © 2015 IEEE. Reproduced in accordance with the publisher's self-archiving policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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