We propose a novel hybrid illumination invariant feature selection scheme for face recognition, which is a combination of geometrical feature extraction and linear subspace projection. By local geometry feature enhancement technique, neighborhood histogram equalization (NHE) in our experiment, some illegible edges due to week illumination will be enhanced effectively. Then we applied classic li...

The synthesis of an effective multi-category nonlinear classifier with the capability to output calibrated posterior probabilities to enable post-processing is of great significance in practical recognition situations in that the posterior probability reflects the assessment uncertainty. In this paper, a multi-scale nonparametric and parametric hybrid recognition strategy is developed for this ...

This paper presents a new method for improving face recognition performance under difficult conditions. Specifically, a new image representation scheme is proposed which is derived from the YCrQ colour space using principal component analysis (PCA) followed by Fisher linear discriminant analysis (FLDA). A multi-scale local feature, LBP-DWT, is used for face representation which is computed by e...

When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null space (irregular) and those in the range space (regular) of the within-class scatter matrix. Recently, regularization techniques, which alleviate the over-fitting to the training set, have been used to further improve ...

An “electronic nose” has been used for the detection of adulterations of sesame oil. The system, comprising 10 metal oxide semiconductor ensors, was used to generate a pattern of the volatile compounds present in the samples. Prior to different supervised pattern recognition treatments, eature extraction techniques were employed to choose a set of optimal discriminant variables. Principal compo...

Biometric technologies are the primary tools for certifying identity of individuals. But cost of sensing hardware plus degree of physical invasion required to obtain reasonable success are considered major drawbacks. Nevertheless, the signature is generally accepted as one means of identification. We present an approach on signature recognition using face recognition algorithms to obtain class ...

Multi-view face detection plays an important role in many applications. This paper presents a statistical learning method to extract features and construct classifiers for multi-view face detection. Specifically, a recursive nonparametric discriminant analysis (RNDA) method is presented. The RNDA relaxes Gaussian assumptions of Fisher discriminant analysis (FDA), and it can handle more general ...

Multi-view face detection plays an important role in many applications. This paper presents a statistical learning method to extract features and construct classifiers for multi-view face detection. Specifically, a recursive nonparametric discriminant analysis (RNDA) method is presented. The RNDA relaxes Gaussian assumptions of Fisher discriminant analysis (FDA), and it can handle more general ...