Towards generating realistic synthetic fingerprint images

Abstract

Synthetic fingerprint generation has two major advantages. First, it is possible to create arbitrarily large databases for research purposes e.g. of a million or a billion fingerprints at virtually no cost and without legal constraints. Secondly, together with the generated fingerprint images comes additional ground truth information for free such as e.g. the corresponding minutiae template. However, recently it has been shown that existing methods in the literature synthesize images with unrealistic minutiae configurations, usually not visible to the naked eye of an expert. In this paper, we propose an algorithm called Realistic Fingerprint Creator (RFC) for the generation realistic synthetic fingerprint images, which, as a core ingredient, involves a selection procedure how to choose the most ‘realistic’ synthetic fingerprints to build a database. We have performed a test of realness comparing prints synthesized by RFC and real fingerprints, and we have observed that the proposed RFC is the first method which produces artificial fingerprints that pass this test due to their realistic minutiae configuration.