Showing papers by "Vincenzo Piuri published in 2015"

Touchless Fingerprint Biometrics

Abstract: Offering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting. The most accurate current biometric technologies in touch-based fingerprint-recognition systems require a relatively high level of user cooperation to acquire samples of the concerned biometric trait. With the potential for reduced constraints, reduced hardware costs, quicker acquisition time, wider usability, and increased user acceptability, this book argues for the potential superiority of touchless biometrics over touch-based methods. The book considers current problems in developing high-accuracy touchless recognition technology. It discusses factors such as shadows, reflections, complex backgrounds, distortions due to perspective effects, uncontrolled finger placement, inconstant resolution of the ridge pattern, and reconstruction and processing of three-dimensional models. The last section suggests what future work can be done to increase accuracy in touchless systems, such as intensive studies on extraction and matching methods and three-dimensional analytical capabilities within systems. In a world where usability and mobility have increasing relevance, Touchless Fingerprint Biometrics demonstrates that touchless technologies are also part of the future. A presentation of the state of the art, it introduces you to the field and its immediate future directions.

Dependability certification of services: a model-based approach

Abstract: The advances and success of the Service-Oriented Architecture (SOA) paradigm have produced a revolution in ICT, particularly, in the way in which software applications are implemented and distributed. Today, applications are increasingly provisioned and consumed as web services over the Internet, and business processes are implemented by dynamically composing loosely coupled applications provided by different suppliers. In this highly dynamic context, clients (e.g., business owners or users selecting a service) are concerned about the dependability of their services and business processes. In this paper, we define a certification scheme that allows to verify the dependability properties of services and business processes. Our certification scheme relies on discrete-time Markov chains and awards machine-readable dependability certificates to services, whose validity is continuously verified using run-time monitoring. Our solution can be integrated within existing SOAs, to extend the discovery and selection process with dependability requirements and certificates, and to support a dependability-aware service composition.

Automatic Classification of Acquisition Problems Affecting Fingerprint Images in Automated Border Controls

Abstract: Automated Border Control (ABC) systems are technologies designed to increase the speed and accuracy of the identity verifications performed at international borders. A great number of ABCs deployed in different countries use fingerprint recognition techniques because of their high accuracy and user acceptability. However, the accuracy of fingerprint recognition methods can drastically decrease in this application context due to user-sensor interaction factors. This paper presents two main contributions. The first of them consists in an experimental evaluation performed to search the main negative aspects that could affect the usability and accuracy in ABCs based on fingerprint biometrics. The mainly considered aspects consists in the presence of luggage and cleanness of the finger skin. The second contribution consists in a novel approach for automatically identifying the type of user-sensor interaction that caused quality degradations in fingerprint samples. This method uses a specific feature set and computational intelligence techniques to detect non-idealities in the acquisition process and to suggest corrective actions to travelers and border guards. To the best of our knowledge, this is the first method in the literature designed to detect problems in user-sensor interaction different from improper pressures on the acquisition surface. We validated the proposed approach using a dataset of 2880 images simulating different scenarios typical of ABCs. Results shown that the proposed approach is feasible and can obtain satisfactory performance, with a classification error of 0.098.

Guest Editorial Special Issue on Big Data Analytics and Management in Internet of Things

Abstract: The papers in this special issue provide a highly exciting opportunity to explore the interdisciplinary nature of the management of Internet of Things (IoT) and big data analytics. Both IoT and big data keep making headlines everywhere, drawing a large amount of research interest, a fast expanding universe of applications, and highlighting unprecedented challenges. On one hand, the IoT has been generating widespread research interest across a variety of technical areas, including the sensor network management, data communication, temporal and spatial data analysis, and visualization. On the other hand, big data are providing innovative solutions addressing the challenges posed by data volume, velocity, variety, and veracity, known as the 4Vs. Instead of being overwhelmed by these issues, researchers and scholars are making significant progress in generating value out of big data. One such effort is to exploit the synergies between IoT and big data, so that both have increased impact. This issue is designed to present innovative ideas and emerging solutions in this new interdisciplinary area.

Advanced design of Automated Border Control gates: Biometric system techniques and research trends

Abstract: Last few years have witnessed an ever-increasing demand of border crossing, whose processing introduces the need to speed-up the clearance process at the Border Crossing Points (BCP). Automated Border Control (ABC) gates, or shortly e-Gates, can verify the identity of the travelers crossing the borders by exploiting their biometric traits, without the need of a constant human intervention. Biometric technologies have a relevant impact on the improvement of efficiency, effectiveness and security of the checking processes. Automated biometric recognition can increase the border processing throughput of the BCP, as well as facilitate the clearance procedures. To grant the passage of the border, the e-Gate compares the biometric samples of the traveler stored into the electronic document with live acquisitions. This paper presents the latest substantial advances in the design of e-Gates. In particular, it presents the Biometric Verification System in detail, including its hardware and software components, as well as the procedures followed during the biometric verification of the traveler's identity. We address the complex issue of measuring the performance of an ABC system, considering the real applicability of the figures of merit usually adopted in biometric system's evaluation. To complete the view of the current e-Gates, we highlight the main challenges and the research trends relating to the biometric systems currently used in e-Gates.

Automated Border Control Systems: Biometric Challenges and Research Trends

Abstract: Automated Border Control ABC systems automatically verify the travelers' identity using their biometric information, without the need of a manual check, by comparing the data stored in the electronic document e.g., the e-Passport with a live sample captured during the crossing of the border. In this paper, the hardware and software components of the biometric systems used in ABC systems are described, along with the latest challenges and research trends.

On the use of fuzzy logic in dependable cloud management

Abstract: The effective and efficient use of dependable cloud infrastructures requires the agreement between users and cloud providers on resources, services, operating conditions, and features as well as the mapping of users' requirements onto the cloud architecture. In this paper, we identify the different ways in which fuzzy logic can be profitably adopted in performing these tasks, providing flexibility in capturing users' needs and dealing with complex architectures and conflicting or hardly-satisfiable requirements. We specifically put forward the idea of using fuzzy logic at the user-side, to enable the specification of users' needs in crisp or fuzzy ways and their homogenous processing.

Replacement of parameter tuning with simple calculation in adaptive control using “Sigmoid generated fixed point transformation”

Abstract: Lately a systematic method was presented for the generation of whole families of Fixed Point Transformations that can be used in nonlinear adaptive control of Single Input — Single Output (SISO) as well as Multiple Input — Multiple Output (MIMO) systems as alternatives of Lyapunov's direct method. This transformation was called Sigmoid Generated Fixed Point Transformation (SGFPT). This paper introduces new improvements on this alternative approach. It is shown that in contrast to the original Robust Fixed Point Transformation (RFPT), for guaranteeing the global stability of the control, instead of tuning, a simple estimation can be done for one of the adaptive control parameters. The novel method is demonstrated by the adaptive control of a 2 Degree of Freedom (DoF) TORA system. Simulation results validate that the suggested approach is beneficial and ensures satisfactory performance.

Improving OSB wood panel production by vision-based systems for granulometric estimation

Abstract: Oriented Strand Board (OSB) is a kind of engineered wood particle board widely adopted in manufacturing, construction and logistics. The production of OSB panels requires rectangular-shaped wood strands of specific size, arranged in layers to form the so-called “mattress” (mat) and bonded together with glue. The structural properties of the panel rely directly on the layer forming. In particular, the size distribution - namely granulometry - of the strands should fulfill standard measures to reach the mechanical properties expected from the panel. Offline granulometry of particle materials is the most commonly procedure used to evaluate the production process, but it is prone to several drawbacks owing to the manual intervention of human operators. Vision-based systems, instead, allow for performing granulometric analyses in an automatic and contactless manner. We propose a computer vision approach to estimate the granulometry of wood strands. The designed framework analyzes images of a mat of strands placed over a moving conveyor belt, and provides useful information and measurements to enhance the production of OSB panels. Because of the very large amount of wood strands on the mat, particle-overlapping is frequent and represents a main issue for measurement algorithms. In order to overcome this problem, our framework joins image processing and computational intelligence methods, such as edge detection and fuzzy color clustering. We tested the framework with real and synthetic images, useful to variate the conditions of the material's shape. The obtained results demonstrate the ability of our approach to evaluate the granulometry of the strands in real conditions, and robustness against the simulated variations of the production process.

Dependability-Oriented Resource Management Schemes for Cloud Computing Data Centers

Abstract: A major factor in the growth of the Information and Communications Technology has been the widespread use of data centers for deploying and executing web services, business processes, and scientific and e-commerce applications. While some data centers are designed to operate a specific business (e.g., Google’s search engine), others are used as the backbone infrastructure to deliver computing resources as services to hundreds of users (e.g., Amazon’s EC2 service). Relying on data centers for running applications, particularly when resources are delivered to the users as a service, offer significant benefits. For example, applications can benefit significantly from the economy of scale, and users are relieved from buying expensive hardware and software licenses and from maintaining the computing infrastructure.