Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.

Fuzzy modeling based recognition of multi-font numerals

In this paper, we present a new scheme for off-line recognition of multi-font numerals using the Takagi-Sugeno (TS) model. In this scheme, the binary image of a character is partitioned into a fixed number of sub-images called boxes. The features consist of normalized vector distances (gamma) from each box. Each feature extracted from different fonts gives rise to a fuzzy set. However, when we have a small number of fonts as in the case of multi-font numerals, the choice of a proper fuzzification function is crucial. Hence, we have devised a new fuzzification function involving parameters, which take account of the variations in the fuzzy sets. The new fuzzification function is employed in the TS model for the recognition of multi-font numerals.

Modeling geometric rules in object based models:an XML / GML approach

Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

Three-dimensional modeling of the human eye based on magnetic resonance imaging

PURPOSE. A methodology for noninvasively characterizing the three-dimensional (3-D) shape of the complete human eye is not currently available for research into ocular diseases that have a structural substrate, such as myopia. A novel application of a magnetic resonance imaging (MRI) acquisition and analysis technique is presented that, for the first time, allows the 3-D shape of the eye to be investigated fully. METHODS. The technique involves the acquisition of a T2-weighted MRI, which is optimized to reveal the fluid-filled chambers of the eye. Automatic segmentation and meshing algorithms generate a 3-D surface model, which can be shaded with morphologic parameters such as distance from the posterior corneal pole and deviation from sphericity. Full details of the method are illustrated with data from 14 eyes of seven individuals. The spatial accuracy of the calculated models is demonstrated by comparing the MRI-derived axial lengths with values measured in the same eyes using interferometry. RESULTS. The color-coded eye models showed substantial variation in the absolute size of the 14 eyes. Variations in the sphericity of the eyes were also evident, with some appearing approximately spherical whereas others were clearly oblate and one was slightly prolate. Nasal-temporal asymmetries were noted in some subjects. CONCLUSIONS. The MRI acquisition and analysis technique allows a novel way of examining 3-D ocular shape. The ability to stratify and analyze eye shape, ocular volume, and sphericity will further extend the understanding of which specific biometric parameters predispose emmetropic children subsequently to develop myopia. Copyright © Association for Research in Vision and Ophthalmology.

The knowledge-based perspective of risk management in healthcare organisations

The aim of this research is to investigate how risk management in a healthcare organisation can be supported by knowledge management. The subject of research is the development and management of existing logs called "risk registers", through specific risk management processes employed in a N.H.S. (Foundation) Trust in England, in the U.K. Existing literature on organisational risk management stresses the importance of knowledge for the effective implementation of risk management programmes, claiming that knowledge used to perceive risk is biased by the beliefs of individuals and groups involved in risk management and therefore is considered incomplete. Further, literature on organisational knowledge management presents several definitions and categorisations of knowledge and approaches for knowledge manipulation in the organisational context as a whole. However, there is no specific approach regarding "how to deal" with knowledge in the course of organisational risk management. The research is based on a single case study, on a N.H.S. (Foundation) Trust, is influenced by principles of interpretivism and the frame of mind of Soft Systems Methodology (S.S.M.) to investigate the management of risk registers, from the viewpoint of people involved in the situation. Data revealed that knowledge about risks and about the existing risk management policy and procedures is situated in several locations in the Trust and is neither consolidated nor present where and when required. This study proposes a framework that identifies required knowledge for each of the risk management processes and outlines methods for conversion of this knowledge, based on the SECI knowledge conversion model, and activities to facilitate knowledge conversion so that knowledge is effectively used for the development of risk registers and the monitoring of risks throughout the whole Trust under study. This study has theoretical impact in the management science literature as it addresses the issue of incomplete knowledge raised in the risk management literature using concepts of the knowledge management literature, such as the knowledge conversion model. In essence, the combination of required risk and risk management related knowledge with the required type of communication for risk management creates the proposed methods for the support of each risk management process for the risk registers. Further, the indication of the importance of knowledge in risk management and the presentation of a framework that consolidates knowledge required for the risk management processes and proposes way(s) for the communication of this knowledge within a healthcare organisation have practical impact in the management of healthcare organisations.

High performance numerical modeling of ultra-short laser pulse propagation based on multithreaded parallel hardware

The focus of this study is development of parallelised version of severely sequential and iterative numerical algorithms based on multi-threaded parallel platform such as a graphics processing unit. This requires design and development of a platform-specific numerical solution that can benefit from the parallel capabilities of the chosen platform. Graphics processing unit was chosen as a parallel platform for design and development of a numerical solution for a specific physical model in non-linear optics. This problem appears in describing ultra-short pulse propagation in bulk transparent media that has recently been subject to several theoretical and numerical studies. The mathematical model describing this phenomenon is a challenging and complex problem and its numerical modeling limited on current modern workstations. Numerical modeling of this problem requires a parallelisation of an essentially serial algorithms and elimination of numerical bottlenecks. The main challenge to overcome is parallelisation of the globally non-local mathematical model. This thesis presents a numerical solution for elimination of numerical bottleneck associated with the non-local nature of the mathematical model. The accuracy and performance of the parallel code is identified by back-to-back testing with a similar serial version.