On non-invasive 2D and 3D Chromatic White Light image sensors for age determination of latent fingerprints.
The feasibility of 2D-intensity and 3D-topography images from a non-invasive Chromatic White Light (CWL) sensor for the age determination of latent fingerprints is investigated. The proposed method might provide the means to solve the so far unresolved issue of determining a fingerprints age in forensics. Conducting numerous experiments for an indoor crime scene using selected surfaces, different influences on the aging of fingerprints are investigated and the resulting aging variability is determined in terms of inter-person, intra-person, inter-finger and intra-finger variation. Main influence factors are shown to be the sweat composition, temperature, humidity, wind, UV-radiation, surface type, contamination of the finger with water-containing substances, resolution and measured area size, whereas contact time, contact pressure and smearing of the print seem to be of minor importance. Such influences lead to a certain experimental variability in inter-person and intra-person variation, which is higher than the inter-finger and intra-finger variation. Comparing the aging behavior of 17 different features using 1490 time series with a total of 41,520 fingerprint images, the great potential of the CWL technique in combination with the binary pixel feature from prior work is shown. Performing three different experiments for the classification of fingerprints into the two time classes [0, 5 h] and [5, 24 h], a maximum classification performance of 79.29% (kappa=0.46) is achieved for a general case, which is further improved for special cases. The statistical significance of the two best-performing features (both binary pixel versions based on 2D-intensity images) is manually shown and a feature fusion is performed, highlighting the strong dependency of the features on each other. It is concluded that such method might be combined with additional capturing devices, such as microscopes or spectroscopes, to a very promising age estimation scheme.
Research Group Multimedia & Security, Otto-von-Guericke University of Magdeburg, FIN/ITI/AMSL, Universitätsplatz 2, 39106 Magdeburg, Germany. ronny.merkel@iti.cs.uni-magdeburg.de
Ronny
R
Merkel
Stefan
S
Gruhn
Jana
J
Dittmann
Claus
C
Vielhauer
Anja
A
Bräutigam
D003878:Dermatoglyphics; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D006813:Humidity; D021621:Imaging, Three-Dimensional; D008027:Light; D008297:Male; D055641:Mathematical Concepts; D013542:Sweat; D013696:Temperature; D013997:Time Factors; D014466:Ultraviolet Rays; D014919:Wind