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Face recognition algorithms commonly assume
that face images are well aligned and have a similar pose
– yet in many practical applications it is impossible to meet
these conditions. Therefore extending face recognition to unconstrained
face images has become an active area of research.
To this end, histograms of Local Binary Patterns (LBP)
have proven to be highly discriminative descriptors for face
recognition. The face area is first divided into small regions from which Local
Binary Pattern histograms are extracted and concatenated into a
single, spatially enhanced feature histogram efficiently representing the
face image.
We have developed a fast and reliable algorithm for face recognition based on histograms of Local Binary Patterns: the average time required for feature extraction using a 64-by-64 image is 0.0176 seconds.
The proposed approach results extremely suitable for real-time image processing.
Index Terms: Matlab, source, code, LBP, local, binary, pattern, face, recognition, histogram, histograms.
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Figure 1. LBP histogram feature extraction |
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A simple and effective source code for High-Speed LBP Face Recognition System. |
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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 |
2015.01.01 |
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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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High-Speed LBP Face Recognition System - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 30 EUROS (less
than 42 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 High-Speed LBP Face Recognition System. 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.
