DiffFinger: Advancing Synthetic Fingerprint Generation through Denoising Diffusion Probabilistic Models

arXiv:2405.04538v1 Announce Type: cross
Abstract: This study explores the generation of synthesized fingerprint images using Denoising Diffusion Probabilistic Models (DDPMs). The significant obstacles in collecting real biometric data, such as privacy concerns and the demand for diverse datasets, underscore the imperative for synthetic biometric alternatives that are both realistic and varied. Despite the strides made with Generative Adversarial Networks (GANs) in producing realistic fingerprint images, their limitations prompt us to propose DDPMs as a promising alternative. DDPMs are capable of …

abstract arxiv biometric biometric data concerns cs.ai cs.cv cs.lg data datasets demand denoising diffusion diverse images obstacles privacy study synthesized synthetic through type underscore