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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.





Figure 1. Facial thermogram

A simple and effective source code for Infrared Face Recognition System.

Demo code (protected P-files) available for performance evaluation. Matlab Image Processing Toolbox is required.

Major features


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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.

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