New Solutions for an Old Challenge:

In criminal investigations, latent fingerprints are often considered as reliable means of identifying suspects. However, the evidential value of a print is strongly dependent on the knowledge of its age (the time which has passed since deposition). Suspects might admit their previous presence at a crime scene, but often claim to have been there prior to or after the crime. Especially in regard to public or highly-frequented crime scenes, prints might lose their evidential value in this case, potentially leading to dropped charges. Despite its high relevance, the challenge of estimating a latent print's age could not be adequately addressed for 80 years.

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.