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A major approach for iris recognition today is to generate
feature vectors corresponding to individual iris images and
to perform iris matching based on some distance metrics. One of
the difficult problems in feature-based iris recognition is that the
matching performance is significantly influenced by many parameters
in feature extraction process, which may vary depending on
environmental factors of image acquisition. We present
an efficient algorithm for iris recognition using phase-based image
matching. The use of phase components in 2D discrete Fourier transforms
of iris images makes possible to achieve
highly robust iris recognition in a unified fashion with a simple
matching algorithm. Experimental evaluation using an iris image
database clearly demonstrates an efficient matching performance
of the proposed algorithm.
Index Terms: Matlab, source, code, iris recognition, iris matching, iris verification, phase, correlation, Fourier transforms.
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Figure 1. Iris segmentation |
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A simple and effective source code for Iris Recognition Algorithm Using Phase-Based Image Matching. All tests were performed with CASIA Iris Image Database available at http://www.cbsr.ia.ac.cn/IrisDatabase.htm. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Image Processing Toolbox is required. |
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Release |
Date |
Major features |
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1.0 |
2007.08.06 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Iris Recognition Using Phase-Based Image Matching - Release 1.0 - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 80 EUROS (less
than 112 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Iris Recognition Using Phase-Based Image Matching. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 14 SP1. Matlab Image Processing Toolbox is required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
