.: Click here to download :.
A moving average filter averages a number of input samples and produce a single output sample.
This averaging action removes the high frequency components present in the signal. Moving average
filters are normally used as low pass filters. In recursive filtering algorithm, previous output samples
also are taken for averaging. This is the reason why it's impulse response extends to infinity.
We have developed a low computational approach for iris recognition based on 1D moving average
filter. Simple averaging is used to reduce the effects of noise and a significative improvement in
computational efficiency can be achieved if we perform the calculation of the mean in a recursive
fashion.
This code uses an optimized version of Libor Masek's routines for iris segmentation available
here.
Libor Masek, Peter Kovesi. MATLAB Source Code for a Biometric Identification System Based on Iris Patterns.
The School of Computer Science and Software Engineering, The University of Western Australia, 2003.
Index Terms: Matlab, source, code, iris, recognition, moving, average, filter, low, computational.
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Figure 1. Iris pattern |
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A simple and effective source code for Low Computational Iris Recognition Based on Moving Average Filter. |
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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 |
2008.11.08 |
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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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Low Computational Iris Recognition Based on Moving Average Filter - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 95 EUROS (less
than 133 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 Low Computational Iris Recognition Based on Moving Average Filter. 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 2006a. 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.
