In this thesis, non-invasive high-resolution capturing devices are for the first time applied to the age estimation challenge, replacing classical physical or chemical print development techniques. They allow to capture a single print in regular time intervals and to systematically study its degradation behavior. Introducing automated processing methods in the form of a digital pipeline including preprocessing, feature extraction and age estimation techniques, objective age estimates are presented for the first time in this field. Maximum classification performances of different capturing devices between 76% and 86% are achieved for two-class problems. Furthermore, a qualitative influence model on the aging speed of latent prints is designed, forming a prerequisite for future studies.
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