Download Age Factors in Biometric Processing by Michael Fairhurst PDF

By Michael Fairhurst

As biometric-based identity and identification authentication turns into more and more common of their deployment, it turns into vital to contemplate matters on the subject of reliability, usability and inclusion. elements that are really very important during this context are the connection among the character of the measurements extracted from a specific 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 comprise:
* assessment of growing older and biometrics
* social components in getting older and their relevance to biometrics
* utilizing age to reinforce functionality in biometrics
* realizing growing older techniques in key biometric modalities
* modality-related techniques to administration of age factors
* business point of view on biometric age factors
* age prediction from biometrics data
* databases and analytical implications
* usability and ageing
* getting old results and implications for biometric cryptosystems
* destiny demanding situations for structures supply.

Age elements in Biometric Processing offers an outline of this subject for the quickly increasing group of stakeholders in biometrics-based id recommendations in academia, and executive.

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Extra info for Age Factors in Biometric Processing

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Similarly Zaphiris and Ellis (2000) describe an experiment where the response time of computer users belonging to different age groups is evaluated. According to the results, of that study, significant differences in response time were recorded for subjects older than 57 years when compared to subjects with ages less than 36. These results are in agreement with the conclusions reported by Guest (2006) indicating that movement dynamics are affected by ageing. 6 Iris Iris is a tissue that covers the pupil of an eye.

Journal of the Korean Physical Society, vol. 38, issue 3, pp. 268–272. Jaffe N. , Jaffe M. , Jaffe G. F. (1990): Cataract Surgery and Its Complications. 5th edn. St. Louis, CV Mosby, pp. 385–411. , Minut S. (2003): ‘Dental biometrics: Human identification using dental radiographs’. Proceedings of the Audio- and Video-Based Biometric Person Authentication, LNCS 2688. 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.

Within this context the so-called ‘ageing impact factor’ (AIF), which provides an indication of the dependence of certain features to ageing variation, is estimated. According to the results colour-based feature vectors display higher AIF when compared to edge-based and texture-based fingerprint features. Based on the results reported in the literature, there is concrete evidence that fingerprints are affected by ageing. Bearing in mind the widespread use of fingerprints in identity verification applications as well as in forensics, it is essential that the topic of fingerprint ageing effects is further investigated.

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