Local Binary Pattern (LBP) is a traditional descriptor for texture analysis that gained attention in the last decade. Being robust to several properties such as invariance to illumination translation and scaling, LBPs achieved stateof-the-art results in several applications. However, LBPs are not able to capture high-level features from the image, merely encoding features with low abstraction l...

Low back pain has become one of the major reasons from absence from work. The aetiology of LBP is still not fully understood and controversy remains regarding the significance of the influencing factors. Clinical objectivity is consistently increased by isokinetic testing devices whose validation is a major goal in clinical practice. By this means we set up a protocol of examination to better q...

A general texture description model is proposed, using topology related attributes calculated from Local Binary Patterns (LBP). The proposed framework extends and generalises existing LBP-based descriptors like LBP-rotation invariant uniform patterns (LBP), and Local Binary Count (LBC). Like them, it allows contrast and rotation invariant image description using more compact descriptors than cl...

A major issue in computer aided celiac disease diagnosis is the prevalence of substantial intra-class and even intra-image variations. A method which splits the images into a set of smaller ones and finally applies a decision level fusion turned out to be a powerful technique to address these problems and to boost the classification accuracy. This is especially true if using Local Binary Patter...

This paper investigates the problem of learning sets of discriminative patterns from local binary patterns (LBP). Such patterns are usually referred to as ‘dominant local binary patterns’ (DLBP). The strategies to obtain the dominant patterns may either keep knowledge of the patterns labels or discard it. It is the aim of this work to determine which is the best option. To this end the paper st...

This paper presents a new method to combine local and global features for near-duplicate images detection. It mainly consists of three steps. Firstly, the keypoints of images are extracted and preliminarily matched. Secondly, the matched keypoints are voted for estimation of affine transform to reduce false matching keypoints. Finally, to further confirm the matching, the Local Binary Pattern (...

Object tracking in real time videos is a critical task .So far many algorithms have been proposed to overcome the difficulties which arises from noise, occlusions and changes in the foreground object. But still there is a need for an efficient algorithm that can effectively track the object due to its varying position under various ambient conditions. Among various tracking methods, the mean sh...

We present a novel Affine-Gradient based Local Binary Pattern (AGLBP) descriptor for texture classification. It is very hard to describe complicated texture using single type information, such as Local Binary Pattern (LBP), which just utilizes the sign information of the difference between pixel and its local neighbors. Our descriptor has three characteristics: 1) In order to make full use of t...

Face image retrieval is an important issue in the practical applications such as mug shot searching and surveillance systems. However, it is still a challenging problem because face images are fairly similar due to the same geometrical configuration of facial features. In this paper, we present a face image retrieval method which is robust to the variations of face image condition and with high...

Multicast is an efficient paradigm for transmitting data from a sender to a group of receivers. The IEEE 802.11 wireless LANs standards specify how to send multicast frames with no ACK and using one of the Basic Service Set (BSS) rates. This situation has led many researchers to design techniques aiming to improve reliability of a multicasting mechanism. The Leader-Base Protocol (LBP) is one su...