Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP

identification of male and female from facial image allows many useful applications in biometrics, surveillance, and human-computer interaction. This paper presents a robust face feature descriptor for gender classification from facial image. The proposed method is based on the compound local binary pattern (CLBP), an extension of the LBP texture operator. The CLBP operator exploits 2P bits to encode the information of a local neighborhood of P neighbors, where P bits are used to express the sign information and the other P bits are used to express the magnitude information of the differences between the center and the neighbor gray values. The performance of the proposed method has been evaluated using a large dataset comprising 1800 facial images collected from the FERET database. Extensive experiments with support vector machine classifier show the superiority of the CLBP feature descriptor against some well-known texture operators.

A Novel Deterministic Mersenne Prime Numbers Test: Aouessare-El Haddouchi-Essaaidi Primality Test

There has been an increasing interest in prime numbers during the past three decades since the introduction of public-key cryptography owing to the large spread of internet and electronic banking. The largest prime number discovered so far, which is a Mersenne number, has 17,425,170 digits. However, the algorithmic complexity of Mersenne primes test is computationally very expensive. The best method presently known for Mersenne numbers primality testing is Lucas–Lehmer primality test. This paper presents a novel primality test for these numbers, namely, Aouessare-El Haddouchi-Essaaidi primality test, which largely outperforms Lucas-Lehmer test with its very low algorithmic complexity which allows performing much quicker tests with the other advantage of considerable memory requirements savings. Moreover, in the case of a composite number, where this test is negative, it is also possible to decompose the tested number into two factors whose product yields it. It is anticipated that this primality test will be a real progress in the theory of prime numbers and in the conquest of very large prime numbers with the subsequent implication on information security and assurance. Furthermore, this test will also allow factoring very large composite numbers in a very efficient way. General Terms The approach presented in this paper is relevant to number theory, and more specifically to prime numbers theory. This theory is strongly related to information cryptography and, thus, to information security assurance and privacy.

A Review on Injury Severity in Traffic System using Various Data Mining Techniques

Traffic Accidents (RTAs) are a major public health concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. The objective of this study is to evaluate a set of variables that contribute to the degree of injury severity in traffic crashes. The issue of traffic safety has raised great concerns across the globe and it has become one of the key issues challenging the sustainable development of modern traffic and transportation. The study on road traffic accident causes can identify the key factors rapidly, efficiently and provide instructional methods to the traffic accidents prevention and road traffic accidents reduction, which could greatly reduce personal casualty and property loss caused by road traffic accidents. Using the method of traffic data analysis, can improve the road traffic safety management level effectively.

Evaluation of Adaptive Boosting and Neural Network in Earthquake Damage Levels Detection

Load Balancing Through Intermediate Gateway Traffic Sharing Model (IGTSM) For WMN

An Expert System for Diagnosis of Blood Disorder

Persian Named Entity Recognition based with Local Filters

Dynamic Current Mode Logic Realization of Digital Arithmetic Circuits

Moving Object Segmentation using Enhanced Laplacian Thresholding Method for Video Surveillance

Feature Point Selection using Structural Graph Matching for MLS based Image Registration

Image registration is a method of determining a mapping or a transformation that relates positions in one image, to the corresponding positions in the other images under considerations. The process of registration depends on the homologous control points that are selected from the source and the target images. This paper focuses on the use of the structural information of an image, for selecting control points, as it remains the same even when it undergoes most of the transformation and illumination changes. The points thus obtained are then given to the Moving Least Squares (MLS) based registration technique reported earlier by the authors [11].