A High-level Optimum Design Methodology for Multimodal Biometric Systems

Abstrac

A low-cost neural-based approach for wood types classification

In many applications such as the furniture and the wood panel production, the classification of wood kinds can provide relevant information concerning the aspect, the properties and the preparation procedures of the products. Usually, the wood kind classification is made by trained operators, but this solution suffers of important drawbacks: it is time consuming and it has low repeatability/accuracy since the classification is related to the operator experience and fatigue. In the literature, some attempts to solve this applicative problem by automatic systems are present, but, unfortunately, these solutions present complex measures and setups. In this paper, we present a novel approach for wood kinds classification based on a neural network system which exploits the emitted spectrum of the wood samples filtered with a bank of low-cost optical filters coupled with a set of photo detectors. The structure of the proposed system can be directly implemented in an embedded low-cost system. The results of the system simulations are very satisfactory and they demonstrate that this approach is feasible and very promising

Selective and private access to outsourced data centers

The advancements in the Information Technology and the rapid diffusion of novel computing paradigms have accelerated the trend of moving data to the cloud. Public and private organizations are more often outsourcing their data centers to the cloud for economic and/or performance reasons, thus making data confidentiality an essential requirement. A basic technique for protecting data confidentiality relies on encryption: data are encrypted by the owner before their outsourcing. Encryption however complicates both the query evaluation and enforcement of access restrictions to outsourced data. In this chapter, we provide an overview of the issues and techniques related to the support of selective and private access to outsourced data in a scenario where the cloud provider is trusted for managing the data but not for reading their content. We therefore illustrate methods for enforcing access control and for efficiently and privately executing queries (at the server side) over encrypted data. We also show how the combined adoption of approaches supporting access control and for efficient query evaluation may cause novel privacy issues that need to be carefully handled

Fingerprint local analysis for high-performance minutiae extraction

The paper presents a novel approach to identify the minutiae present in a fingerprint image based on the analysis of the local properties. The typical patterns of minutiae called ridge termination and bifurcation are identified by studying the intensity along squared paths in the image. The presented algorithm works both on grey-level image and binarized image and, despite its simplicity, it achieves good accuracy and it can be a good candidate to be implemented in hardware or executed on simple hardware architectures, for example in biometric systems embedded in portable applications such as cellular phones and smart cards

A high-level optimum design methodology for multimodal biometric systems

Biometric systems are designed by expert developers who look - with trial-and-error approaches - for reasonable solutions by considering the available hardware architecture, some - possibly conflicting - quality goals, and the application constrains. Typically drawbacks of these approaches are waste of time and results far from the optimum. We propose a new design methodology for multimodal biometric systems that applies high-level system design techniques to better structure the design procedure. The proposed methodology avoids the drawbacks of the common design practice and allows to create a flexible general-purpose and effective design environment for multimodal biometric systems

Genetic techniques for pattern extraction in particle boards images

Time-to-market and high product quality standards are pushing the use of automatic visual inspection systems for defect detection in a wide broad of applications. The defect detection of particle boards requires the identification of all the printed and natural wood defects that can occur. The availability of information about the particle board to inspect (e.g. the pattern used to print the surface of the board) could increase heavily the defect detection capability of a quality assessment system. Nevertheless, most of the times the pattern is not available during the defect detection phase (i.e. when the pattern changes quickly or when printing and defect detection are not performed by the same company). We propose a novel approach for pattern extraction based on genetic techniques to identify the printing pattern that can be used in defect classification systems. Experimental results show the valuable pattern extraction capabilities of the proposed approach

Robust fingerprint detection for access control

The paper presents a robust novel approach for access control based on the identification of the minutiae present in a fingerprint image based on the analysis of the local properties cards. The classical patterns of minutiae called ridge termination and bifurcation are identified by studying the intensity along squared paths in the image. The presented algorithm works both on grey-level image obtained directly scanning the fingerprint and binarized image and, despite its simplicity, it achieves good accuracy and can be a good candidate to be implemented in hardware or embedded on simple biometric hardware architectures or portable biometric applications such as cellular phones and smart cards

A biometric verification system addressing privacy concerns

Biometric techniques are more and more exploited in order to fasten and make more reliable the identification process. Recently, many proposals have been formulated combining cryptography and biometrics in order to increase the confidence in the system when biometric templates are stored for verification. In this work we present a biometric authentication technique based on the combination of multiple biometric readings. The authentication control can be performed offline and the stored identifier does not disclose any information on the biometric traits of the identified person, so that even in case of loss or steal of the document, privacy is guaranteed