Face Recognition Technology


Face recognition

Face Recognition Based on PCA

DCT-ANN Face Identification

Wavelet-ANN Face Recognition

Face Recognition Based on Polar Frequency Features

Face Recognition Based on FisherFaces

Face Recognition Based on Local Features

Face Recognition in Fourier Space

WebCam Face Identification

Face Recognition Based on Overlapping DCT

Face Recognition Based on Statistical Moments

Face Recognition Based on Nonlinear PCA

Face Recognition Based on Hierarchical Dimensionality Reduction

Fusion of Low-Computational Global and Local Features For Face Recognition

SVD-Based Face Recognition

Correlation Filters Face Verification

ICA Face Recognition

3D Face Recognition

Infrared Face Recognition

Octave Face Recognition

PHP Face Recognition

JAVA Face Recognition

LBP Face Recognition System

HMM Face Recognition System

NMF Face Recognition System

Face matching

Face Identification Based on CPD

GA MACE Face Verification

External resources

Advanced Source Code .Com

Neural Networks .It

Genetic Algorithms .It

Iris Recognition .It

Sparse Representation for Facial Thermogram Recognition

Download now Matlab source code
Requirements: Matlab, Matlab Image Processing Toolbox.

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.

Release 1.0 Date 2012.06.15
Major features:

Face Recognition . It Luigi Rosa mobile +39 3207214179 luigi.rosa@tiscali.it