Online ISSN
2047-4946
Print ISSN
2047-4938
IET Biometrics
Volume 1, Issue 2, June 2012
Volumes & issues:
Volume 1, Issue 2
June 2012
Editorial: Spirit of IET Biometrics
- Author(s): J.L. Wayman
- Source: IET Biometrics, Volume 1, Issue 2, p. 91 –93
- DOI: 10.1049/iet-bmt.2012.0023
- Type: Article
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- Author(s): C. Rathgeb and A. Uhl
- Source: IET Biometrics, Volume 1, Issue 2, p. 94 –104
- DOI: 10.1049/iet-bmt.2011.0001
- Type: Article
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In this study a statistical attack against fuzzy commitment schemes is presented. Comparisons of different pairs of binary biometric feature vectors yield binomial distributions, the standard deviations of which are bounded by the entropy of biometric templates. In case error correction consists of a series of chunks, like in the vast majority of approaches, helper data become vulnerable to statistical attacks. Error-correction codewords are bound to separate parts of a binary template among which biometric entropy is dispersed. As a consequence, chunks of the helper data are prone to statistical significant false acceptance. In experimental evaluations the proposed attack is applied to different iris-biometric fuzzy commitment schemes retrieving cryptographic keys at alarming low effort. - Author(s): C. Gottschlich and C.-B. Schönlieb
- Source: IET Biometrics, Volume 1, Issue 2, p. 105 –113
- DOI: 10.1049/iet-bmt.2012.0003
- Type: Article
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To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors’ new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors’ knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. - Author(s): A. Pflug and C. Busch
- Source: IET Biometrics, Volume 1, Issue 2, p. 114 –129
- DOI: 10.1049/iet-bmt.2011.0003
- Type: Article
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The possibility of identifying people by the shape of their outer ear was first discovered by the French criminologist Bertillon, and refined by the American police officer Iannarelli, who proposed a first ear recognition system based on only seven features. The detailed structure of the ear is not only unique, but also permanent, as the appearance of the ear does not change over the course of a human life. Additionally, the acquisition of ear images does not necessarily require a person's cooperation but is nevertheless considered to be non-intrusive by most people. Owing to these qualities, the interest in ear recognition systems has grown significantly in recent years. In this survey, the authors categorise and summarise approaches to ear detection and recognition in 2D and 3D images. Then, they provide an outlook over possible future research in the field of ear recognition, in the context of smart surveillance and forensic image analysis, which they consider to be the most important application of ear recognition characteristic in the near future. - Author(s): S. Pillay ; A. Ariyaeeinia ; P. Sivakumaran ; M. Pawlewski
- Source: IET Biometrics, Volume 1, Issue 2, p. 130 –135
- DOI: 10.1049/iet-bmt.2012.0001
- Type: Article
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This paper presents a new approach to condition-adjusted T-norm (CT-Norm) for speaker verification under significant mismatched noise conditions. The study is motivated by the fact that, though the standard CT-Norm method offers enhanced accuracy under mismatched data conditions, its effectiveness reduces with the increased severity of such conditions. The proposed approach attempts to address this challenge by providing a more effective reduction of data mismatch through the incorporation of multi-signal-to-noise ratio (SNR) universal background models (UBMs). The effectiveness of the proposed approach is demonstrated through experiments based on examples of real-world noise. It is shown that the superiority of the approach over CT-Norm is particularly significant for such excessive levels of test data degradation considered in the study as 5 dB SNR and below. The paper provides a description of the characteristics of the proposed approach and details the experimental analysis of its effectiveness under different noise conditions. - Author(s): M. Erbilek and M. Fairhurst
- Source: IET Biometrics, Volume 1, Issue 2, p. 136 –147
- DOI: 10.1049/iet-bmt.2012.0011
- Type: Article
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This paper investigates and explores the impact of physical ageing in signature biometrics. Experimental performance evaluation, using three different signature databases, is carried out to provide some new insights into the relationship between different practical factors, in particular clarifying the impact on recognition performance of the data collection protocols used and the use of the feature pools underpinning the signature processing. This analysis provides an alternative perspective from which to explore and manage physical ageing effects in signature biometrics. The paper demonstrates that the proposed strategy maximises system accuracy while minimising the performance differential across a population which is heterogeneous with respect to age, and across different databases. The results presented suggest that adoption of the strategy proposed can render a template update procedure less critical than hitherto expected.
Statistical attack against fuzzy commitment scheme
Oriented diffusion filtering for enhancing low-quality fingerprint images
Ear biometrics: a survey of detection, feature extraction and recognition methods
Effective speaker verification via dynamic mismatch compensation
Framework for managing ageing effects in signature biometrics
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