# IET Biometrics

## Filter Results

Displaying Results 1 - 3 of 3
• ### Subface hidden Markov models coupled with a universal occlusion model for partially occluded face recognition

Publication Year: 2012, Page(s):149 - 159
Cited by:  Papers (2)
| |PDF (1016 KB)

In this study, a novel face recognition framework based on the grammatical face models has been proposed to tackle partial occlusion problem. The grammatical face model represents a face by five isolated subface, forehead, eyes, nose, mouth and chin models in cooperation with occlusion models. With the creations of subface and occlusion models, the authors then define a facial grammar to m... View full abstract»

• ### Adaptive discriminative metric learning for facial expression recognition

Publication Year: 2012, Page(s):160 - 167
Cited by:  Papers (4)
| |PDF (391 KB)

The authors propose in this study a new adaptive discriminative metric learning method for facial expression recognition. Although a number of methods have been proposed for facial expression recognition, most of them apply the conventional Euclidean distance metric to measure the similarity/dissimilarity of face expression images and cannot effectively characterise such similarity/dissimilarity o... View full abstract»

• ### Optimisation of biometric ID tokens by using hardware/software co-design

Publication Year: 2012, Page(s):168 - 177
Cited by:  Papers (1)
| |PDF (566 KB)

In current society, the necessity of recognising people is increasing every day. Logical or physical access is restricted to authorised users, which in many cases have to provide tokens where their personal information is stored. At the same time, biometrics proposes a feasible solution for the recognition problem. The combination of both solutions is coming up front. However, up till now, owing t... View full abstract»

## Aims & Scope

The field of biometric recognition - automated recognition of individuals based on their behavioural and biological characteristics - has now reached a level of maturity where viable practical applications are both possible and increasingly available. The biometrics field is characterised especially by its interdisciplinarity since, while focused primarily around a strong technological base, effective system design and implementation often requires a broad range of skills encompassing, for example, human factors, data security and database technologies, psychological and physiological awareness, and so on. Also, the technology focus itself embraces diversity, since the engineering of effective biometric systems requires integration of image analysis, pattern recognition, sensor technology, database engineering, security design and many other strands of understanding.

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## Meet Our Editors

Editor-in-Chief
Michael Fairhurst
University of Kent
UK

Publisher
IET Research Journals
iet_bmt@theiet.org