.: Click here to download :.
Human face recognition is currently a very active
research area with focus on ways to perform robust and
reliable biometric identification. Face recognition, the art
of matching a given face to a database of known faces, is a
non-intrusive biometric method that dates back to the
1960s. In efforts going back to far earlier times, people
have tried to understand which facial features help us
perform recognition tasks, such as identifying a person,
deciding on an individual's age and gender, and classifying
facial expression and even beauty. A recognition system
has to be invariant both to external changes, like
environmental light, partial occlusions and the person's
position and distance from the camera, and internal
deformations, like facial expression and aging. Because
most commercial applications use large databases of faces,
recognition systems have to be computationally efficient.
We have developed a code to perform face identification using
a Genetic algorithm-optimized Minimum Average Correlation Energy
(MACE) filtering technique.
The performances of the proposed algorithm are
evaluated using Facial Expression Database collected at
the Advanced Multimedia Processing Lab at Carnegie
Mellon University (CMU). Database consists of 13
subjects, each with 75 images. The size of each image is
64×64 pixels, with 256 grey levels per pixel. A 5×5 filter has been
designed using genetic algorithms. With GA Feature Correlation we have
achieved an EER equal to 3.70%.
Index Terms: Matlab, source, code, correlation, filters, face, recognition, identification, system, MACE, GA, genetic, algorithm.
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Figure 1. Facial image |
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A simple and effective source code for GA MACE Face Recognition. |
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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 |
2011.07.08 |
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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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GA MACE Face Recognition - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 400 EUROS (less
than 560 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 GA MACE Face Recognition. 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.
