Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.695707
Title: Novel template ageing techniques to minimise the effect of ageing in biometric systems
Author: Pg Hj Mohd Yassin, D. K. Hayati Bte
ISNI:       0000 0004 5990 7678
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2016
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Abstract:
Effect of ageing on biometric systems and particularly its impact on face recognition systems. Being biological tissue in nature, facial biometric trait undergoes ageing. As a result developing biometric applications for long-term use becomes a particularly challenging task. Despite the rising attention on facial ageing, longitudinal study of face recognition remains an understudied problem in comparison to facial variations due to pose, illumination and expression changes. Regardless of any adopted representation, biometric patterns are always affected by the change in the face appearance due to ageing. In order to overcome this problem either evaluation of the changes in facial appearance over time or template-age transformation-based techniques are recommended. By using a database comprising images acquired over a 5-years period, this thesis explores techniques for recognising face images for identify verification. A detailed investigation analyses the challenges due to ageing with respect to the performance of biometric systems. This study provides a comprehensive analysis looking at both lateral age as well as longitudinal ageing. This thesis also proposes novel approaches for template ageing to compensate the ageing effects for verification purposes. The approach will explore both linear and nonlinear transformation mapping methods. Furthermore, the compound effect of ageing with other variate (such as gender, age group) are systematically analysed. With the implementation of the novel approach, it can be seen that the GAR (Genuine Accept Rate) improved significantly.
Supervisor: Hoque, Sanaul ; Deravi, Farzin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.695707  DOI: Not available
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