In this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fMRI) data. In the preprocessing step, the number of fMRI time points is reduced using principal component analysis (PCA). Then, independent component analysis (ICA) is used for further data analysis. It estimates independent components (ICs) of...

One of the challenges faced by visually impaired persons is the recognition of currency. Mobile phones are becoming more affordable and are being used by the visually impaired community to help them in their everyday lives. This paper investigates the Local Binary Patterns (LBP) as a method to recognise Trinidad and Tobago currency notes. A mobile application was developed and the effectiveness...

As the features from the traditional Local Binary patterns (LBP) and Local Directional Patterns (LDP) are found to be ineffective for face recognition, we have proposed a new approach derived on the basis of Information sets whereby the loss of information that occurs during the binarization is eliminated. The information sets expand the scope of fuzzy sets by connecting the attribute and the c...

A good Arabic handwritten recognition system must consider the characteristics of Arabic letters which can be explicit such as the presence of diacritics or implicit such as the baseline information (a virtual line on which cursive text are aligned and/join). In order to find an adequate method of features extraction, we have taken into consideration the nature of the Arabic characters. The pap...

Abstract Local Binary Pattern (LBP) is a simple yet very efficient texture operator which labels the pixels of an image by threshold the neighbourhood of each pixel and considers the result as a binary number. Due to its discriminative power and computational simplicity, LBP texture operator has become a popular approach in various applications. It can be seen as a unifying approach to the trad...

This paper presents a new Feature Local Binary Patterns (FLBP) that encodes the information of both local texture and features. The features are broadly defined by, for example, the edges, the Gabor wavelet features, the color features, etc. Specifically, a binary image is first derived by extracting feature pixels from a given image I, and then a distance vector field is obtained by computing ...

Local binary patterns (LBP) has been very successful in a number of areas, including texture analysis and face analysis. Recently, local quantized patterns (LQP) was proposed to use vector quantization to code complicated patterns with a large number of neighbors and several quantization levels. It uses lookup table technique to map patterns into the corresponding indices. In this paper, we pro...

Despite the great deal of progress during the recent years, face spoofing detection is still a focus of attention. In this paper, an effective, simple and time-saving countermeasure against video-based face spoofing attacks based on LBP (Local Binary Patterns) and multiscale DCT (Discrete Cosine Transform) is proposed. Adopted as the low-level descriptors, LBP features are used to extract spati...

In [1], Abegaz et. al compared hybrid genetic and evolutionary feature selection (GEFeS) and weighting (GEFeW) on feature sets obtained by Eigenface, LBP, and oLBP feature extraction methods. GEFeS and GEFeW were implemented using a Steady-State Genetic Algorithm (SSGA). In this paper, we extend the work performed in [1] and compared GEFeS and GEFeW implementations using SSGAs and Estimation of...

Local Binary Patterns (LBP) is a widely used approach for medical image analysis. Limitations of the LBP operator are its sensitivity to noise and its boundedness to first derivative information. These limitations are usually balanced by extensions of the classical LBP operator (e.g. the Local Ternary Pattern operator (LTP) or the Extended LBP (ELBP) operator). In this paper we present a generi...