Dr. Ali Mohammed Sahan IT Dept., Technical College of Management, Middle Technical University, Baghdad, Iraq AbstractFace recognition process in human perception utilizes two kinds of features. The first are global features used to describe the whole face image, while the second are local features used to describe finer details of the face. The combined face recognition methods stimulate the te...

Recognizing avatar faces is a challenge and very important issue for terrorism and security experts. Recently some avatar face recognition techniques are proposed but they are still limited. In this paper, we propose a novel face recognition technique based on discrete wavelet transform and Adapted Median Binary Pattern (AMBP) operator to recognize avatar faces from different virtual worlds. Th...

The local binary pattern approach has evolved to represent a significant breakthrough in texture analysis, outperforming earlier methods in many applications. Perhaps the most important property of the LBP operator in real-world applications is its tolerance against illumination changes. Another equally important is its computational simplicity, which makes it possible to analyze images in chal...

In this paper we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be a promising descrip...

Recently, a spatiotemporal local binary pattern operator from three orthogonal planes (LBP-TOP) was proposed for describing and recognizing dynamic textures and applied to facial expression recognition. In this paper, we extend the LBP-TOP features to multi-resolution spatiotemporal space and use them for describing facial expressions. AdaBoost is utilized to learn the principal appearance and ...

Local Binary Patterns (LBP) is a widely used approach for medical image analysis. Limitations of the LBP operator are its sensitivity to noise and its boundedness to first derivative information. These limitations are usually balanced by extensions of the classical LBP operator (e.g. the Local Ternary Pattern operator (LTP) or the Extended LBP (ELBP) operator). In this paper we present a generi...

Local binary pattern (LBP) is sensitive to noise. Noise-resistant LBP (NRLBP) addresses this problem by thresholding local neighboring pixels into three-valued states (i.e., 0, 1 and uncertain bits) recovering bits via an error-correction mechanism. In paper, we extend NRLBP deal with color images propose a robust image descriptor called Color context (CCBP). CCBP, employ scale neighbor progres...

Human faces undergo considerable amount of variations with aging. This variation being experienced in facial texture and shape with different ages of a particular subject makes recognition of faces very difficult. However, most existing Face Recognition Systems (FRS) suffer from high misclassification of faces because of the large variation in face appearances of the same individual due to agin...

In this paper a new method for detection of lung nodules in CT image is proposed which is robust to noise. For nodule detection, two important steps are followed: feature extraction and classification. For features extraction, some texture features are extracted based on an extended type of Local Binary Pattern (LBP). LBP is one of the most important feature extractor in texture image but one o...

The paper addresses the problem of gender classification from face images. For feature extraction, we propose discrete Overlapping Block Patterns (OBP), which capture the characteristic structure from the image at various scales. Using integral images, these features can be computed in constant time. The feature extraction at multiple scales results in a high dimensionality and feature redundan...