ect 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 signif