Gender is an important demographic attribute. In the context of biometrics, gender information can be used to index databases or enhance the recognition accuracy of primary biometric traits. A number of studies have demonstrated that gender can be automatically deduced from face images. However, few studies have explored the possibility of automatically estimating gender information from finger...

It is a critical problem to find the commerce quickly and accuracy. Information from different sources can improve the retrieval performance. In this paper, we proposed a combination algorithm of color descriptor, LBP texture descriptor and HOG shape descriptor for commerce image retrieval. The commerce image retrieval experiments on commerce image dataset PI 100 indicate the combination can bo...

Traditionally, iris recognition systems capture iris images in the 700 to 900nm range. It is within these ranges that researchers have found the most viable iris textures for iris recognition. Recently, there has been an interest for exploration of spectrum ranges that falls outside of these traditional ranges. In this work, we will explore the performance of feature extraction techniques on a ...

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 ...

This paper purposes a new method for selecting the most discriminant rotation invariant patterns in local binary patterns and local ternary patterns. Our experiments show that a selection based on variance performs better than the recently proposed method of using dominant local binary patterns (DLBP). Our method uses a random subspace of patterns with higher variance. Features are transformed ...

In this paper a real-time surface inspection method based on texture features is introduced. The proposed approach is based on the Local Binary Pattern (LBP) texture operator and the Self-Organizing Map (SOM). A very fast software implementation of the LBP operator is presented. The SOM is used as a powerful classifier and visualizer. The efficiency of the method is empirically evaluated in two...

s: October 20, 2014 Page 1 of 32 ABSTRACTS LUMBAR SPINE PELVIC GIRDLES LUMBAR SPINE PELVIC GIRDLE

Local Binary Patterns (LBP) have been well exploited for facial image analysis recently. In the existing work, the LBP histograms are extracted from local facial regions, and used as a whole for the regional description. However, not all bins in the LBP histogram are necessary to be useful for facial representation. In this paper, we propose to learn discriminative LBP-Histogram (LBPH) bins for...

Recently, a nonparametric approach to texture analysis has been developed, in which the distributions of simple texture measures based on local binary patterns (LBP) are used for texture description. The basic LBP encodes 256 simple feature detectors in a single 3x3 operator. This paper shows that a properly selected subset of patterns encoded in LBP forms an efficient and robust texture descri...

In this paper we propose two novel rotation invariant local texture descriptors. They are based on Local Binary Pattern (LBP), which is one of the most effective and frequently used texture descriptor. Although LBP efficiently captures the local structure, it is not rotation invariant. In the proposed methods, a dominant direction is evaluated in a circular neighbourhood and the descriptor is c...