Universal Fingerprint Generation: Controllable Diffusion Model with Multimodal Conditions

arXiv:2404.13791v1 Announce Type: new
Abstract: The utilization of synthetic data for fingerprint recognition has garnered increased attention due to its potential to alleviate privacy concerns surrounding sensitive biometric data. However, current methods for generating fingerprints have limitations in creating impressions of the same finger with useful intra-class variations. To tackle this challenge, we present GenPrint, a framework to produce fingerprint images of various types while maintaining identity and offering humanly understandable control over different appearance factors such as fingerprint class, …

abstract arxiv attention biometric biometric data class concerns cs.ai cs.cv current data diffusion diffusion model fingerprints however impressions limitations multimodal privacy recognition synthetic synthetic data type universal