Facial Expression Recognition is one of the active research area in the field of Human Machine Interaction (HMI) because of its several applications such as human emotion analysis, stress level and lie detection. In this paper, an algorithm for facial expression recognition has been proposed which integrate the Local Binary Patterns (LBP), Gabor filter and Principal Component Analysis (PCA). Th...

A face recognition method based on long Haar-like filters is proposed. This filter takes a vector form whose components consist of 1 and −1. Although the learning of the filter is basically by the principal component analysis (PCA), our approach lies in constructing a highpass filter with 1 and −1 as filter coefficients. This approach yields a combinatorial optimization problem. Since the probl...

Denoising is always a challenging problem in magnetic resonance imaging (MRI) and is important for clinical diagnosis and computerized analysis, such as tissue classification and segmentation. The noise in MRI has a Rician distribution. Unlike additive Gaussian noise, Rician noise is signal dependent, and separating the signal from the noise is a difficult task. In this paper, we propose a usef...

This paper describes three methods (logAbout, homomorfic filter and wavelet) for illumination normalization and compares their contributions for posterior face recognition using Principal Component Analysis (PCA).

Mechanical vibrations are often the principal cause of image degradation. Low temporal-frequency mechanical vibrations involve random image degradation that depends on the instant of exposure. Exact restoration requires the calculation of a specific filter unique to each vibrated image. To calculate the restoration filter for each image, one needs the specific optical transfer function unique t...

Much attention has recently been given to the construction of signaladapted orthonormal filter banks designed to optimize a particular objective function such as coding gain or a multiresolution criterion. For certain classes of filter banks, the optimum solution is a principal component filter bank (PCFB), which is simultaneously optimal for several objectives including the ones mentioned abov...

Discriminative filtering is a pattern recognition technique which aim maximize the energy of output signal when a pattern is found. Looking improve the performance of filter response, was incorporated the principal component analysis in discriminative filters design. In this work, we investigate the influence of the quantity of principal components in the performance of discriminative filtering...

The online object tracking is a challenging problem because any useful approach must handle various nuisances including illumination changes and occlusions. Though a lot of work focus on observation models by employing sophisticated approaches for contaminated data, they commonly assume that the samples for updating observation model are uncorrupted or can be restored in updating. For instance,...

Microwave remote sensing provides an excellent means for mapping polar sea ice extent. In this study, a new algorithm for polar sea ice mapping is developed for use with the SeaWinds instrument. The approach utilizes a priori information within the framework of Bayes detection to produce sea ice extent maps. Statistical models for sea ice and ocean are represented in histograms which are filter...