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Facial expression recognition has many potential applications which has attracted the attention of researchers in the last decade. Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition. This paper represents an approach of combining the shape and appearance features to form a hybrid feature vector. We have extracted Pyramid...
The images of lace textile are particularly difficult to be analyzed in digital form using classical image processing techniques. The major reasons of this difficulty emerge from the complex nature of lace which generally has different textures in its constituents like the background and patterns. In this paper, we study the behavior of Image Histogram (HistI) and Local Binary Patterns (LBP) on image...
The Local Binary Pattern (LBP) is an effective image descriptor. However, this descriptor has limitations in some of challenging issues in texture analysis, such as invariance to scaling, rotation, viewpoint variations and non-rigid deformations. In order to overcome these demerits of LBP, the paper proposed a weighted and adaptive LBP-based texture descriptor. Adaptive definition of circular neighboring...
In face recognition, there are great challenges with variations arising from illumination, expression and other factors. Since the fractional Fourier transform feature is robust to illumination and expression variations and has been used in face recognition area, we propose a novel algorithm to face recognition with the local region histogram of the two dimensional fractional Fourier transform (2D-FrFT)...
In the paper a novel approach to the problem of eye blink detection in video sequences is proposed. The introduced method is utilizing the technique of Local Binary Patterns (LBP), which enables to build a descriptor capturing the features of the current eye state. In the initial step, the histogram of LBP describing the open eye is constructed and afterwards it serves as a template, which is compared...
Handwritten signatures are one of the most widely used biometrics, particularly in financial and legal transactions. Offline Signature verification is still one of the most challenging problems in biometrics. In this study, we have evaluated the performance of different classifiers for offline signature verification based upon local binary patterns feature set. The feature vector is formed by dividing...
Mammographic breast density refers to the prevalence of fibroglandular tissue as it appears on a mammogram. Breast density is not only an important risk for developing breast cancer but can also mask abnormalities. Breast density information can be used for planning individualized screening and treatment. In this work, statistical distributions of different texture descriptors and their combination...
The development of a fully automatic facial expression recognition system is an open problem. Its implications are very important, with applications ranging from machine intelligence and interaction to psychology research. In order to obtain a viable system, it is necessary to get valid parameters to characterize the facial expression in an image or a video sequence. Several different techniques have...
Recently, several papers have proposed pseudo dynamic methods for automatic handwritten signature verification. Each of these papers uses texture measures of the gray level signature strokes. This paper explores the usefulness of local binary pattern (LBP) and local directional pattern (LDP) texture measures to discriminate off-line signatures. A comparison between several texture normalizations is...
We combine sparse representation with a multiresolution histogram face descriptor to create a powerful representation method for face recognition. The multi resolution histogram descriptor is based on local binary patterns or local phase coding to achieve invariance to various types of image degradation phenomena. By its nature, the histogram descriptor is also robust to geometric misalignment of...
Contemporary 2D face recognition is still a challenging work, especially when lighting varies. Thus, many works of resolving illumination variation in face recognition have been proposed, in the past decades. In this paper, we proposed Wavelet Local Binary Patterns Histogram Specification as a preprocessing technique for illuminated face recognition. Based on wavelet analysis, an illuminated facial...
In this paper, A new approach to face recognition is constructed by combining the local binary pattern (LBP) operator and locally linear embedding (LLE). LBP is an effective low-cost image descriptor to extract facial texture feature which represents the local structure of face images. LLE is an excellent non-linear data dimensionality reduction method. Its main optimization only involves a sparse...
A novel approach to facial expression recognition with Marginal Fisher Analysis (MFA) on Local Binary Pattern (LBP) is proposed. Firstly, each image is transformed by an LBP operator and then divided into 3 ?? 5 non-overlapping blocks. The features of facial expression images are formed by concatenating the LBP histogram of each block. Secondly, MFA algorithm based on Graph Embedding (GE) is applied...
In this paper, we propose a novel nonuniform division strategy for wearing-glasses face recognition based on Gabor filters and Local Binary Patterns (LBP) operator. The proposed method, which looks forward to weaking the effect of eyeglasses variation, divides a facial image into nonuniform regions, followed by using Gabor filters and LBP. Our experimental results on FERET and Yale database reveal...
Performance of a face recognition system has not been satisfied due to the illumination variation on facial image. Thus, there were many works that dealing with illumination compensation in face recognition in the past decades. One of the important techniques is to remove the illumination component based on the illumination reflectance model. In this paper, a facial image illumination invariant algorithm...
In the medical domain, experts usually look at specific anatomical structures to identify the cause of a pathology, and therefore they can largely benefit from automated tools that retrieve relevant slice(s) from a patient's image volume in diagnosis. Accordingly, this paper introduces a novel search and retrieval work for finding relevant slices in brain MR (magnetic resonance) volumes. As intensity...
Estimating the age exactly and then producing the younger and older images of the person is important in security systems design. In this paper local binary patterns are used to classify the age from facial images. The local binary patterns (LBP) are fundamental properties of local image texture and the occurrence histogram of these patterns is an effective texture feature for face description. In...
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