Texture analysis is one of the important as well as useful tasks in image processing applications. Many texture models have been developed over the past few years and Local Binary Patterns (LBP) is one of the simple and efficient approach among them. A number of extensions to the LBP method have been also presented but the problem remains challenging in feature vector generation and comparison....

Cross-domain ground-based cloud classification is a challenging issue as the appearance of cloud images from different cloud databases possesses extreme variations. Two fundamental problems which are essential for cross-domain ground-based cloud classification are feature representation and similarity measurement. In this paper, we propose an effective feature representation called transfer of ...

Features such as Local Binary Patterns (LBP) and Local Ternary Patterns (LTP) have been very successful in a number of areas including texture analysis, face recognition and object detection. They are based on the idea that small patterns of qualitative local gray-level differences contain a great deal of information about higher-level image content. Existing local pattern features use hand-spe...

In this paper, we present an approach for crowd detection based on an ensemble of classifiers which employ several feature representation schemes of crowd images, including, local ternary patterns, local binary patterns, and features based on the spatial gray level dependency matrix. A Support Vector Machine classifier is trained on each of these feature vectors. Classifier predictions are then...

Face recognition is one of the important and popular visual recognition problem due to its challenging nature and its diverse set of applications. That‘s why face recognition is attracted by many researchers. Methods based on Local Binary Pattern (LBP) are widely used for face recognition in the literature, and it is sensitive to noise. To address this present paper utilized the powerful local ...

Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussians at each pixel [8], to kernel density estimates at each pixel [1], and more recently to joint domainrange density estimates that incorporate spatial information [7]. Another line of work has shown the benefits of in...

Local Binary Patterns and various derivatives of the method have been widely used in the field of texture recognition over the past 15 years. A restriction of these methods is their variance with respect to affine transformations of an image. This is caused by the fixed circular neighborhood and the fixed support area of sampling points. The main approach to deal with affine transformations suc...