The aim of this work is to investigate illumination compensation and normalization in eigenspace-based face recognition by carrying out an independent comparative study among several pre-processing algorithms. This research is motivated by the lack of direct and detailed comparisons of those algorithms in equal working conditions. The results of this comparative study intend to be a guide for t...

The way a person is moving his/her head and facial parts (such as the movements of the mouth when a person is talking) defines so called facial dynamics and characterizes personal behaviors. An emerging direction in automatic face analysis consists of also using such dynamic cues, in addition to facial structure, in order to enhance the performance of static image based methods. This is inspire...

In this paper, we propose a novel face recognition technique based on discrete wavelet transform and Local Binary Pattern (LBP) with adapted threshold to recognize avatar faces in different virtual worlds. The original LBP operator mainly thresholds pixels in a specific predetermined window based on the gray value of the central pixel of that window. As a result the LBP operator becomes more se...

In this paper, we present a novel face recognition method called Multi-scale block Center-Symmetric Local Binary Pattern (MCS-LBP). The face recognition process mainly consists of three phase: face representation, feature extraction, and classification. However, the most important phase is extraction, in which unique features of the face image are extracted. The Center-Symmetric Local Binary Pa...

In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...

A novel descriptor able to improve the classification capabilities of a typical pattern recognition system is proposed in this paper. The introduced descriptor is derived by incorporating two efficient region descriptors, namely image moments and Local Binary Patterns (LBP), commonly used in pattern recognition applications, in the last decades. The main idea behind this novel feature extractio...

Research into facial expression recognition has predominantly been based upon near frontal view data. However, a recent 3D facial expression database (BU-3DFE database) has allowed empirical investigation of facial expression recognition across pose. In this paper, we investigate the effects of pose from frontal to profile view on facial expression recognition. Experiments are carried out on 10...

This paper proposes a novel facial expression recognition method composed of two main steps: offline step and online step. The offline step selects the most salient facial patches using mutual information technique. The online step relies on the already selected patches to identify the facial expression using an SVM classifier. In both steps, the LBP operator was used to extract facial expressi...

Finger vein recognition is a promising biometric recognition due to its some advantages. For a finger vein recognition system, feature extraction is a critical step for the final recognition. In our previous work, we proposed Personalized Best Bit Map(PBBM) which selected the stable bits from LBP. Although PBBM achieve a better performance, it still contains some useless bits for recognition. I...

We develop a parameter-free face recognition algorithm which is insensitive to large variations in lighting, expression, occlusion, and age using a single gallery sample per subject. We take advantage of the observation that equidistant prototypes embedding is an optimal embedding that maximizes the minimum one-against-the-rest margin between the classes. Rather than preserving the global or lo...