-Nowadays face recognition plays an important role in today’s world. It has achieved greater importance in the field of information security, law enforcement and surveillance. Now this face recognition approach is applied to many areas like Airport security, Driver’s License, Passport, Customs and Immigration. In face recognition Local appearance based methods had achieved greater performance. ...

In the last two decades, an increasing number of illumination pretreatment methods and local feature descriptors have been proposed to address the issue of face recognition under different illumination conditions. Although these have achieved impressive results, the problem of how to maximize the reduction of the effect of variable lighting on captured images remains open. We assume that face i...

Textures play an important role in recognition of images. This paper investigates the efficiency of performance of three texture based feature extraction methods for face recognition. The methods for comparative study are Grey Level Co_occurence Matrix (GLCM), Local Binary Pattern (LBP) and Elliptical Local Binary Template (ELBT). Experiments were conducted on a facial expression database, Japa...

In this paper we propose two novel rotation invariant local texture descriptors. They are based on Local Binary Pattern (LBP), which is one of the most effective and frequently used texture descriptor. Although LBP efficiently captures the local structure, it is not rotation invariant. In the proposed methods, a dominant direction is evaluated in a circular neighbourhood and the descriptor is c...

This paper presents an efficient algorithm for face recognition using the local binary pattern (LBP) and random forest (RF). The novelty of this research effort is that a modified local binary pattern (MLBP), which combines both the sign and magnitude features for the improvement of facial texture classification performance, is applied. Furthermore, RF is used to select the most important featu...

Iris-based personal identification has attracted much attention in recent years. Almost all the state-of-the-art iris recognition algorithms are based on statistical classifier and local image features, which are noise sensitive and hardly to deliver perfect recognition performance. In this paper, we propose a novel iris recognition method, using the histogram of local binary pattern for global...