An Investigation into the Effects of Image Resolution on a Facial-Image-Based Personal Authentication System

The issues associated with image resolution in automated authentication or identification systems has become one of the important challenges for researchers' in biometrics. The aim of this thesis is to investigate the effect of variable resolutions on the performance of a Facial-Image-Based Person Authentication System. Image resolution may vary significantly especially in uncontrolled acquisition environments or when sensing from a distance and so on. The detail available in the data thus reduces which may deteriorate the performance of such system. In this project we investigated the impact on system accuracy when image resolution is gradually reduced by a given factor. As a remedy, we investigated different methods for increasing image resolution prior to using those images for authentication and compared the relative gains in accuracy. The main procedure of the face image authentication system based on comparing landmarks of the face remains the same. In this study, we found that several issues related to image resolutions might have an impact on the recognition rate performance such as facial expressions, image background, and others. The influence of image resolution on the recognition rate increases roughly with the increasing resolution at a specific degree, high-image resolution would not be good for recognition rate always; reducing high image resolution makes it easier to achieve high face recognition rates

Dental Biometrics: Human Identification Using Dental Radiograph

Biometric is the science and innovation of measuring and analyzing biological information.In information technology, biometric refers to advancements that measures and analyzes human body attributes,for example,DNA, eye retinas, fingerprints and irises,face pattern,voice patterns,and hand geometry estimations,for identification purposes.The primary motivation behind scientific dentistry is to distinguish expired people,for whom different method for recognizable proof(e.g.,unique finger impression,face,and so on.)are not accessible.Dental elements survives most of the PM events which may disrupt or change other body tissues,e.g. casualties of motor vehicles mishaps,fierce violations,and work place accident,whose bodies could be deformed to such a degree,that identification even by a family member is neither desirable nor reliable.Dental Biometric utilises dental radiographs to distinguish casualties.The radiographs procured after the casualty's demise are called post-mortem radiograph and the radiograph obtained when the casualty was alive is called ante-mortem radiograph.The objective of dental biometric is to match the unidentified individual's post-mortem radiograph against a database of labelled antemortem radiograph.This thesis proposes a novel method for the contour extraction from dental radiographs.The proposed algorithm of Active Contour Model or the Snake model is used for this purpose. A correctly detected contour is essential for proper feature extraction.This thesis only works on the contour detection.The method has been tested on some radiographs images and is found to produce desired output.However,the input radiograph image may be of low quality,may suffer a clear separation between two adjacent teeth.In that case the method will not be able to produce a satisfactory result.There is a need of pre-processing(e.g. contrast enhancement) before the active contour detection model can be applie

A Software Engineered Voice-Enabled Job Recruitment Portal System

The inability of job seekers to get timely job information regarding the status of the application submitted via conventional job portal system which is usually dependent on accessibility to the Internet has made so many job applicants to lose their placements. Worse still, the epileptic services offered by Internet Service Providers and the poor infrastructures in most developing countries have greatly hindered the expected benefits from Internet usage. These have led to cases of online vacancies notifications unattended to simply because a job seeker is neither aware nor has access to the Internet. With an increasing patronage of mobile phones, a self-service job vacancy notification with audio functionality or an automated job vacancy notification to all qualified job seekers through mobile phones will simply provide a solution to these challenges. In this paper, we present a Voice-enabled Job Recruitment Portal (JRP) System. The system is accessed through two interfaces – the voice user’s interface (VUI) and web interface. The VUI was developed using VoiceXML and the web interface using PHP, and both interfaces integrated with Apache and MySQL as the middleware and back-end component respectively. The JRP proposed in this paper takes the hassle of job hunting from job seekers, provides job status information in real-time to the job seeker and offers other benefits such as, cost, effectiveness, speed, accuracy, ease of documentation, convenience and better logistics to the employer in seeking the right candidate for a job

Advanced Biometrics with Deep Learning

Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others

With renewables for energy security

Taking into account the possible future exhaustion of fossil energy sources, the actual and near danger of climate change, the drastic increase of the greenhouse gases in the last 200 years, as well as the growing need for sustainable development, consumption and liveable environment, the increasing necessity of renewable energy sources becomes clear. Utilization of these energy sources have to acquire a bigger role in the field of energy supply, in order to enhance the energy security of Hungary, to decline the energy import dependence, to reduce the negative environmental impacts, and to recover the economy. The world’s hunger for energy is growing exponentially; this is why it is crucial to establish feasibility scenarios in the next decades, which are able to meet these expectations, and to increase the safety of the energy supply

With renewables for energy security

Taking into account the possible future exhaustion of fossil energy sources, the actual and near danger of climate change, the drastic increase of the greenhouse gases in the last 200 years, as well as the growing need for sustainable development, consumption and liveable environment, the increasing necessity of renewable energy sources becomes clear. Utilization of these energy sources have to acquire a bigger role in the field of energy supply, in order to enhance the energy security of Hungary, to decline the energy import dependence, to reduce the negative environmental impacts, and to recover the economy. The world’s hunger for energy is growing exponentially; this is why it is crucial to establish feasibility scenarios in the next decades, which are able to meet these expectations, and to increase the safety of the energy supply

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity