This paper proposes color local binary pattern and fractional Fourier Transform features for face recognition. The YCbCr Color space model is used in this approach. Fractional Fourier Transform features and local binary pattern features are used for face recognition. kNN classifier is applied to face recognition phase.

Face detection is one of the hottest research topics of the field of pattern recognition, image processing, machine vision, and etc. This paper proposes a novel method for fast and reliable face detection, especially in complex background. Firstly, the Haar features of the training image are extracted, and then the training image is divided into small blocks to extract local binary pattern (LBP...

In many image processing applications, such as segmentation and classification, the selection of robust features descriptors is crucial to improve the discrimination capabilities in real world scenarios. In particular, it is well known that image textures constitute power visual cues for feature extraction and classification. In the past few years the local binary pattern (LBP) approach, a text...

Recently, there are increasing interests in inferring mirco-expression from facial image sequences. Due to subtle facial movement of micro-expressions, feature extraction has become an important and critical issue for spontaneous facial micro-expression recognition. Recent works usually used spatiotemporal local binary pattern for micro-expression analysis. However, the commonly used spatiotemp...

Local Binary Pattern (LBP) is a very efficient local descriptor for describing image texture. In this paper, we propose a novel face recognition technique based on wavelet transform and the least square estimator to enhance the classical LBP. First, Wavelet transform is used to decompose a given image into four kinds of frequency images from which the features of that image can be extracted. Th...

Local Binary Pattern (LBP) is invariant to the monotonic changes in the grey scale domain. This property enables LBP to present a texture descriptor that can be useful in applications dealing with the local illumination changes. However, the existing versions of LBP are not able to handle image illumination changes, especially in outdoor environments. These non-patterned illumination changes di...

in this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fmri) data. in the preprocessing step, the number of fmri time points is reduced using principal component analysis (pca). then, independent component analysis (ica) is used for further data analysis. it estimates independent components (ics) of...

In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbou...

The proposal of this study is to analyze the texture pattern recognition over the local jet space looking forward to improve the texture characterization. Local jets decompose the image based on partial derivatives allowing the texture feature extraction be exploited in different levels of geometrical structures. Each local jet component evidences a different local pattern, such as, flat region...