Image retrieval is one of the main topics in the field of computer vision and pattern recognition. Local descriptors are gaining more and more recognition in recent years as these descriptors are capable enough to identify the unique features, which suitably and uniquely describe any image for recognition and retrieval. One of the popular and efficient frame works for capturing texture informat...

In this paper, we propose a novel face recognition technique based on discrete wavelet transform and Local Binary Pattern (LBP) with adapted threshold to recognize avatar faces in different virtual worlds. The original LBP operator mainly thresholds pixels in a specific predetermined window based on the gray value of the central pixel of that window. As a result the LBP operator becomes more se...

Local Binary Patterns (LBP) is a non-parametric descriptor whose purpose to effectively summarize local image configurations. It has generated increasing interest in many aspects including facial analysis, vision detection, expression demographic classification, etc. recent years and proven useful various applications. This paper presents binary pattern based face recognition technology using V...

In this work, we introduce a new fusion framework for multispectral face recognition in the textures space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. The proposed texture space is based on the use of LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) techniques. Also, a new adaptive texture descriptor is presented....

In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting eac...

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...

A novel local binary pattern (LBP) based adaptive diffusion is presented for image denoising. The LBP operator unifies traditionally divergent statistical and structural models of region analysis. We use LBP textons to classify an image around a pixel into noisy, homogenous, corner and edge regions. According to different types of regions, a variable weight is introduced into the diffusion equa...

To improve the efficiency of facial expression recognition, this paper puts forward a kind of recognition algorithm based on local binary pattern (LBP) and empirical mode decomposition (EMD). First of all, process the empirical mode decomposition into the preprocessing facial image, and bring forward many a high frequency images instead of the original image; then, divide the sub domain of the ...

There are many Local texture features each very in way they implement and each of the Algorithm trying improve the performance. An attempt is made in this paper to represent a theoretically very simple and computationally effective approach for face recognition. In our implementation the face image is divided into 3x3 sub-regions from which the features are extracted using the Local Binary Patt...

Osteoarthritis (OA) causes progressive degeneration of articular cartilage and pathological changes in subchondral bone. These changes can be assessed volumetrically using micro-computed tomography (μCT) imaging. The local descriptor, i.e. local binary pattern (LBP), is a new alternative solution to perform analysis of local bone structures from μCT scans. In this study, different trabecular bo...