Richard Guest

Developing algorithms to enhance the sensitivity of cancellation tests of visuospatial neglect

We describe a set of algorithms that enhance the sensitivity of cancellation tests used in assessing visuospatial neglect. The algorithms can be readily implemented on a computer and can provide temporal and nontemporal data on strategies used during cancellation. We also present preliminary results from a group of 68 right-hemisphere brain-damaged patients and 12 age-matched control participants, which demonstrate the clinical significance of the measures we have defined.

The repeatability of signatures

Signatures are the most widely used form of legally binding identification and authentication. The repeatability of a persons signature underpins its recognition and hence usefulness in everyday authentication situations. This study aims to assess the stability of a set of common features used for analysing signatures both within a single capture session and over time (multiple sessions). Secondly, the physical characteristics of signatures which result in the most repeatable performance for each feature are also analyzed. These results have implications for biometric signature verification systems and the document forensic field in that it gives an indication as to the stability of features leading potentially to improved performance and the types of features that should be analyzed given particular characteristics of the signature under investigation.

A synthesised word approach to word retrieval in handwritten documents

Recent technological advances have enhanced the computer-based indexing and searching of digitised printed books. The performance now achievable in this domain, however, does not at present extend to handwritten texts which inherently contain more significant letter-based variation within their content. Furthermore, in most studies that address the handwritten text retrieval problem, a large training dataset is required which, very often, influences the context and search lexicon. In this paper a novel method is described to overcome the training data problem using a character-based modelling (termed grapheme spectrum) approach and a word modelling technique (termed synthesised word) enabling the retrieval of keywords that have not explicitly been seen in the training set. When tested on an illustrative historical manuscript the performance of the proposed word retrieval technique shows a clear advantage over existing methods.

Computer recording of standard tests of visual neglect in stroke patients

Objective: To determine whether a computer-based method for recording standardized assessment of neglect identifies abnormalities in the ‘process’ as well as in the ‘outcome’ of such tasks. Design: Prospective sequential assessment of patients admitted to a stroke rehabilitation unit. Subjects: All consecutive patients with right-sided cerebrovascular accident confirmed on computerized tomography (CT) scan including 30 patients with neglect, 57 patients without neglect. An age-matched control group of 13 subjects. Intervention: All patients were tested using the standard Rivermead Behavioural Inattention Test (BIT) and by computer recording of two standard tests for assessing neglect (line bisection and Alberts test). Age-matched controls were tested using computer recording of the two standard tests. Main outcome measures: Neglect was defined using the BIT with a cut-off score of 129. Computer recording measured the ‘outcome’ of tasks, i.e. the deviation from midline and omissions in cancellation, as well as the ‘process’ of tasks, i.e. time between cancellations, components of cancellation time including premovement, movement and drawing time, and the starting point for cancellation. Results: The computer recording identified significant differences in ‘outcome’ and ‘process’ which distinguished neglect from non-neglect patients. There were significant differences between non-neglect patients and age-matched controls with regard to ‘process’ measures but not with regard to ‘outcome’ measures. Conclusions: Computer recording of standard tests for assessing neglect identifies novel impairments with regard to the process of carrying out tasks. These impairments may be used to investigate changes in neglect with time, the response of neglect to treatment and to explore further the neuropsychological changes associated with neglect in stroke patients.

Biosecure reference systems for on-line signature verification: a study of complementarity

In this paper, we present an integrated research study in On-line Signature Verification undertaken by several teams that participate in the BioSecure Network of Excellence. This integrated work started during the First BioSecure Residential Workshop, has as main objective the development of an On-line Signature Verification evaluation platform. As a first step, four On-line Signature Verification Systems based on different approaches are evaluated and compared following the same experimental protocol on MCYT signature database, which is the largest existing on-line western signature database publicly available with 16500 signatures from 330 clients. A particular focus of work documented in this paper is multi-algorithmic fusion in order to study the complementarity of the approaches involved. To this end, a simple fusion method based on the Mean Rule is used after a normalization phase.RésuméDans cet article, nous présentons un travail commun sur la vérification de signature enligne, réalisé par 4 équipes qui participent au Réseau d’Excellence BioSecure. Ce travail commun, débuté durant le premier « Workshop » résidentiel, a pour principal objectif le développement d’une plateforme d’évaluation pour la vérification de la signature en-ligne. Tout d’abord, quatre systèmes de vérification de signature en-ligne basés sur différentes approaches sont évalués et comparés en utilisant le même protocole expérimental sur la base de signatures MCYT, la plus grande base existante de signatures en-ligne disponible, avec 16500 signatures de 330 personnes. Ensuite, l’accent est mis sur la fusion multi-algorithmique afin d’étudier la complémentarité des approches impliquées. Pour cela, une méthode de fusion simple est utilisée, basée sur une moyenne des scores après une phase de normalisation.

A New Method for the Synthesis of Signature Data With Natural Variability

The collection of human biometric test data for system development and evaluation within any chosen modality generally requires significant time and effort if data are to be obtained in workable quantities. To overcome this problem, techniques to generate synthetic data have been developed. This paper describes a novel technique for the automatic synthesis of human handwritten-signature images, which introduces modeled variability within the generated output based on positional variation that is naturally found within genuine source data. The synthesized data were found to generate similar verification rates to those obtained using genuine data with the use of a commercial verification engine, thereby indicating the suitability of the data synthesized by using this method for a wide range of application scenarios.

A Method for the Synthesis of Dynamic Biometric Signature Data

This paper describes a novel method for the generation of synthetic handwritten signatures, in the form of a series of time-stamped pen data channels, for use in dynamic signature verification experimentation. The technique introduces modelled variability within the generated data based on variation that is naturally found within genuine source data. Experimentation using the SVC2004 dataset and a commercial signature verification engine shows that the synthesized data achieves comparative verification performance to the use of genuine data.

Developing a generic approach to online automated analysis of writing and drawing tests in clinical patient profiling

Writing and drawing tests are widely used in the clinical environment for the diagnosis of a variety of neuro-psychological conditions. Conventional assessment of these tests involves the inspection by trained assessors of the completed patient response. This article describes the development of a computer-based framework for data capture, automated feature analysis, and result reporting for a range of drawing- and writing-based test batteries. In developing this framework, we have exploited the commonality between tasks while allowing for both flexibility in configuration across condition-specific testing requirements and extensibility for future test development. Using the two example clinical conditions of visuospatial neglect and dyspraxia, we illustrate the advantages of utilizing a computer-based analysis system, describe a structured approach to system implementation, and demonstrate the generality of this implementation for different conditions of interest, which extends to feature selection and design.

Intelligent agents for the management of complexity in multimodal biometrics

Current approaches to personal identity authentication using a single biometric technology are limited, principally because no single biometric is generally considered both sufficiently accurate and user-acceptable for universal application. Multimodal biometrics can provide a more adaptable solution to the security and convenience requirements of many applications. However, such an approach can also lead to additional complexity in the design and management of authentication systems. Additionally, complex hierarchies of security levels and interacting user/provider requirements demand that authentication systems are adaptive and flexible in configuration. In this paper we consider the integration of multimodal biometrics using intelligent agents to address issues of complexity management. The work reported here is part of a major project designated IAMBIC (Intelligent Agents for Multimodal Biometric Identification and Control), aimed at exploring the application of the intelligent agent metaphor to the field of biometric authentication. The paper provides an introduction to a first-level architecture for such a system, and demonstrates how this architecture can provide a framework for the effective control and management of access to data and systems where issues of privacy, confidentiality and trust are of primary concern. Novel approaches to software agent design and agent implementation strategies required for this architecture are also highlighted. The paper further shows how such a structure can define a fundamental paradigm to support the realisation of “universal access” in situations where data integrity and confidentiality must be robustly and reliably protected .

Diagnosis of Visuo-Spatial Neglect Using Dynamic Sequence Features from a Cancellation Task

Abstract: Visuo-spatial neglect is recognised as a major barrier to recovery following a stroke or head injury. A standard clinical assessment technique to assess the condition is a pencil-and-paper based cancellation task. Traditional static analysis of this task involves counting the number of targets correctly cancelled on the test sheet. Using a computer-based test capture system, this paper presents the novel application of using a series of standard pattern recognition techniques to examine the diagnostic capability of a number of dynamic features relating to the sequence in which the targets were cancelled. While none of the individual dynamic features is as sensitive to neglect as the conventional static analysis, a series of standard multi-dimensional feature analysis techniques are shown to improve the classification accuracy of the dynamic properties of task execution, and hence the sensitivity to the detection of neglect and the validity of this novel application. Combining the outcome of the dynamic sequence-based features with the conventional static analysis further improves the overall sensitivity of the two cancellation tasks included in this study. The algorithmic nature of the methodology for feature extraction objectively and consistently assesses patients, thereby improving the repeatability of the task.