A First Public Research Collection of High-Resolution Latent Fingerprint Time Series for Short- and Long-Term Print Age Estimation

Abstract

The creation of publicly available image databases for the signal processing community is a very time-consuming, yet immensely valuable task, enabling scientific progress by providing the opportunity of an objective comparison and reproduction of results. This paper presents for the first time a public research collection of high-resolution latent fingerprint time series for age estimation, captured from a pool of 116 different test subjects. It comprises ten different sets with a total of 2,618-time series (117,384 scans), varying between capturing devices (CWL and CLSM), data types (intensity vs. topography), aging periods (short-term aging: 24h, long-term aging: 0.5y - 3y) and resolutions (1,270 ppi - 180,142 ppi). Most series are annotated with donor information (age, gender) and capturing conditions (scan parameters, ambient temperature and humidity). The data is anonymized (using partial prints only) and an organizational revocation mechanism is included to assure non-identifiability of donors in the future.

Existing System

Binary Pixel Sub-Tendencies, Contactless Confocal Laser Scanning Microscopy (CLSM).

Proposed System

The aim of this paper is to provide for the first time a publicly available research collection of high-resolution latent print time series for scientific research (including baseline performances) while at the same time ensuring certain standards of data privacy protection. It therefore contributes to the IEEE SPS initiative to support open data collections for reproducible research in forensics. It paves the way for organizing challenges and motivates further research in this emerging field.

Architecture

BLOCK DIAGRAM