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Face recognition is a rapidly growing research area due to increasing demands for security in
commercial and law enforcement applications. We have depeloped a fast and reliable face recognition techniques based on two-dimensional (2D)
images in the infrared (IR) spectra. Face recognition systems based on visual images have reached a significant level of maturity with some practical success.
However, the performance of visual face recognition may degrade under poor illumination conditions or for subjects of various skin colors.
IR imagery represents a viable alternative to visible imaging in the search for a robust and
practical identification system. While visual face recognition systems perform relatively reliably
under controlled illumination conditions, thermal IR face recognition systems are advantageous
when there is no control over illumination or for detecting disguised faces. Face recognition using 3D images is another active area of face recognition,
which provides robust face recognition
with changes in pose. Recent research has also demonstrated that the fusion of different imaging
modalities and spectral components can improve the overall performance of face recognition.
Sparse representation, also known as compressed sensing, has been applied recently to image-based face
recognition and demonstrated encouraging results. Under this framework, each face is represented by a set of features, which sufficiently characterize each individual. With
the prior knowledge that faces of the same individual are
similar to each other, a probe face can be considered as
being well approximated by linearly combining the k reference faces of the same individual in the training set.
Code has been tested on Terravic Facial IR Database. The Terravic Facial Infrared database
contains total no. of 20 classes (19 men and 1 woman)
of 8-bit gray scale JPEG thermal faces. Size of the database is 298MB and images with
different rotations are left, right and frontal face images also available with different items
like glass and hat.
Index Terms: Matlab, source, code, infrared, ir, thermogram, face, recognition, verification, matching, sparse, representation.
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Figure 1. Facial thermogram |
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A simple and effective source code for Infrared 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 |
2012.06.15 |
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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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Infrared Face Recognition System. Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 120 EUROS (less
than 168 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 Infrared 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 14 SP1. 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.
