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The theory of advanced correlation filters has evolved from
the literature of optical pattern recognition in the last two
decades; they have proved effective classifiers in a number of applications, among them biometric recognition and
automatic target recognition. Correlation filter designs use the image intensity domain
of training examples to compute a class template that produces characteristic correlation outputs to distinguish between authentic users and impostors.
When applying thefilter for testing the authenticity of a new target image, the
output plane is expected to have a shape containing a correlation peak if the image is authentic, but no such peak if the
image belongs to another class. Properties of correlation filter classifiers include graceful degradation, shift invariance
and closed-form solutions.
The code has been tested using fingerprint images taken with an UPEK swipe fingerprint reader with capacitive
sensor and USB 2.0 connection. Database is 16 fingers wide and 8 impressions per finger deep (128 fingerprints in all). We have obtained the
following results:
- One-to-many fingerprint identification: using 2 images for each finger randomly selected for training and the remaining 6 images for testing (totally 32 images for training and 96 images for testing), without any overlapping, we have obtained an error rate smaller than 0.6% (top one error rate).
- One-to-one fingerprint verification: we have obtained an EER equal to 5.6641%.
Index Terms: Matlab, source, code, correlation, filters, AFIS, automated, fingerprint, identification, system.
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Figure 1. Fingerprint image |
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A simple and effective source code for Correlation Filters AFIS. |
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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 |
2011.05.27 |
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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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Correlation Filters AFIS - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 200 EUROS (less
than 280 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 Correlation Filters AFIS. 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.
