Benchmarking Local Orientation Extraction in Fingerprint Recognition

The computation of local orientations is a fundamental step in fingerprint recognition. Although a large number of approaches have been proposed in the literature, no systematic quantitative evaluations have been done yet, mainly due to the lack of proper datasets with associated ground truth information. In this paper we propose a new benchmark (which includes two datasets and an accuracy metric) and report preliminary results obtained by testing four well-known local orientation extraction algorithms.