Age Factors in Biometric Processing by Michael Fairhurst

By Michael Fairhurst

As biometric-based identity and identification authentication turns into more and more common of their deployment, it turns into very important to contemplate concerns on the subject of reliability, usability and inclusion. elements that are relatively very important during this context are the connection among the character of the measurements extracted from a selected biometric modality, the age of the pattern donor, and the influence which age has on physiological and behavioral features invoked in a biometric transaction.

Topics contain:
* evaluation of growing older and biometrics
* social elements in getting older and their relevance to biometrics
* utilizing age to augment functionality in biometrics
* knowing growing older techniques in key biometric modalities
* modality-related techniques to administration of age factors
* commercial viewpoint on biometric age factors
* age prediction from biometrics data
* databases and analytical implications
* usability and ageing
* getting older results and implications for biometric cryptosystems
* destiny demanding situations for platforms supply.

Age elements in Biometric Processing offers an outline of this subject for the speedily increasing neighborhood of stakeholders in biometrics-based identity options in academia, and executive.

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Guildford, UK; pp. 429–437. , Prabhakar S. (2004): ‘An introduction to biometric recognition’. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics, vol. 14, issue 1, pp. 4–20. , Ross A. ) (2008): Handbook of Biometrics, Springer, New York. , Kapadia A. S. (2001): ‘Functional decline in Parkinson disease’. Archives of Neurology, vol. 58, issue 10, pp. 1611–1615. Jeffreys A. , Thein S. L. (1985): ‘Individual-specific ‘‘fingerprints’’ of human DNA’.

Apart from the personal uniqueness of ageing variation, ageing can cause diverse effects for subjects belonging to different genders and ethnic origins. Uncertainty: The process of ageing could be affected by external factors that may not be predictable. For example, the ageing process for a person who experiences a traumatic event in his/her life may influence both the rate and the type of ageing variation for that person. As a result the long-term impact of ageing is highly unpredictable. In Lanitis (2010) a separation of ageing effects into direct and indirect is suggested.

Despite its relative maturity, the field of biometrics still has many unresolved issues, and still needs on-going high-quality research and the continued sharing of knowledge, expertise and ideas. Some evidence for this is the fact that the IET (the publishers of this book) launched in 2012 a new Journal (IET Biometrics [6]) to focus explicitly on the biometrics field in all its diversity. The inevitability of ageing, and the indiscriminate way in which ageing affects each and every potential user of a biometric system, means that this is a topic which should indeed be towards the very top of the research agenda, and is increasingly important with each year that passes.

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