.: Click here to download :.
Most face recognition systems tend to use either global
image features, which describe an image as a whole, or local
features, which represent image patches. Global features
have the ability to generalize an entire object with a
single vector. Consequently, their use in standard classification
techniques is straightforward. Local features, on the
other hand, are computed at multiple points in the image
and are consequently more robust to occlusion and clutter.
However, they may require specialized classification algorithms
to handle cases in which there are a variable number
of feature vectors per image. We have developed a new face recognition
approach that combines both global and local features: this fast
feature extraction method results extremally suitable for low
computational power microprocessors.
The code has been tested with AT&T database achieving an excellent recognition rate of 97.84%
(40 classes, 5 training images and 5 test images for each class, hence there are 200 training
images and 200 test images in total randomly selected and no overlap exists between the training and test images).
Index Terms: Matlab, source, code, face, recognition, matching, global, local, features, feature, dimensionality, reduction.
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Figure 1. Global and local features for face recognition |
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A simple and effective source code for Fusion of Low-Computational Global and Local Features For 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 |
2009.03.28 |
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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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Fusion of Low-Computational Global and Local Features For Face Recognition. Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 150 EUROS (less
than 210 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 Fusion of Low-Computational Global and Local Features For 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.
