The Competitive Coding (CompCode) scheme, which extracts and codes the local dominant orientation as features, has been widely used in finger knuckle print (FKP) verification. However, CompCode may lose some valuable information such as multiple orientation and texture of the FKP image. To remedy this drawback, a novel multiple orientation and texture information integration scheme is proposed ...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...

As a new approach to human identification, fingervein recognition is becoming an active biometric recognition mode. This paper focuses on fingervein recognition system. First, a preprocessing algorithm is used to enhance each fingervein image. Then, an improvement technique of feature extraction based on Monogenic Local Binary Pattern (MLBP) is presented. This novel metric integrates the conven...

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to...

Local feature detection and description have gained a lot of interest in recent years since photometric descriptors computed for interest regions have proven to be very successful in many applications. In this paper, we propose a novel interest region descriptor which combines the strengths of the well-known SIFT descriptor and the LBP texture operator. It is called the center-symmetric local b...

Musculoskeletal ultrasound imaging can be used to investigate the skeletal muscle structure in terms of architecture (thickness, cross-sectional area, fascicle length and fascicle pennation angle) and texture. Gray-scale analysis is commonly used to characterize transverse scans of the muscle. Gray mean value is used to distinguish between normal and pathologic muscles, but it depends on the im...

This paper investigates possibilities for application of Kernel based Extreme Learning Machines (K-ELM) to the problem of multiclass image classification. It is combined with Local Binary Pattern (LBP) image descriptor, to reach highly accurate results. LBP is widely used global image descriptor characterized by compactness and robustness to illumination and resolution changes. Classification i...

Face representation is one of the open problems in face detection. The recently proposed Multi-Block Local Binary Patterns (MBLBP) representation has shown good results for this purpose. Although dissimilarity representation has proved to be effective in a variety of pattern recognition problems, to the best of our knowledge, it has never been used for face detection. In this paper, we propose ...

The statistical approaches such as texture spectrum and local binary pattern methods have been discussed in this paper. The features are extracted by the computation of LBP and Texture Spectrum histogram. A combined approach of LBP with texture spectrum is also proposed further. Experiments of texture feature extraction, classification of textures and similarity-based image-to-image matching ar...