M
Michael Fairhurst
Researcher at University of Kent
Publications - 288
Citations - 3710
Michael Fairhurst is an academic researcher from University of Kent. The author has contributed to research in topics: Biometrics & Artificial neural network. The author has an hindex of 28, co-authored 288 publications receiving 3573 citations. Previous affiliations of Michael Fairhurst include University of Southampton.
Papers
More filters
Journal ArticleDOI
Gabor wavelets and General Discriminant Analysis for face identification and verification
TL;DR: A novel and uniform framework for both face identification and verification is presented, based on a combination of Gabor wavelets and General Discriminant Analysis, and can be considered appearance based in that features are extracted from the whole face image and subjected to subspace projection.
Journal ArticleDOI
The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)
Javier Ortega-Garcia,Julian Fierrez,Fernando Alonso-Fernandez,Javier Galbally,M.R. Freire,Joaquin Gonzalez-Rodriguez,Carmen García-Mateo,J.L. Alba-Castro,Elisardo González-Agulla,Enrique Otero-Muras,Sonia Garcia-Salicetti,Lorene Allano,Bao Ly-Van,Bernadette Dorizzi,Josef Kittler,Thirimachos Bourlai,Norman Poh,Farzin Deravi,Ming Ng,Michael Fairhurst,Jean Hennebert,Andreas Humm,Massimo Tistarelli,Linda Brodo,Jonas Richiardi,Andrezj Drygajlo,Harald Ganster,Federico M. Sukno,Sri-Kaushik Pavani,Alejandro F. Frangi,Lale Akarun,Arman Savran +31 more
TL;DR: A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented, comprised of more than 600 individuals acquired simultaneously in three scenarios: over the Internet, in an office environment with desktop PC, and in indoor/outdoor environments with mobile portable hardware.
Journal ArticleDOI
Multiple classifier decision combination strategies for character recognition: A review
A. F. Rahman,Michael Fairhurst +1 more
TL;DR: This paper explicitly reviews the field of multiple classifier decision combination strategies for character recognition, from some of its early roots to the present day and illustrates explicitly how the principles underlying the application of multi-classifier approaches to character recognition can easily generalise to a wide variety of different task domains.
Journal ArticleDOI
Robust Road Modeling and Tracking Using Condensation
TL;DR: A method for estimating the density of road boundary line segments in the image so that VP detection in an image strip takes into account the detection results in the neighboring image strips, which leads to more accurate detection results.
Journal ArticleDOI
Recognition of Handwritten Bengali Characters: A Novel Multistage Approach
TL;DR: This analysis demonstrates how detection of various high-level features of the Bengali character set might help formulate successful multistage OCR design.