arXiv (Cornell University) · 2017 · 21 citations · 2 references
ComputingComputer ScienceCybersecurityAuthenticationMobile ComputingMobile SecurityAuthentication ArchitectureBiometric AuthenticationDevice AuthenticationDigital AuthenticationDigital IdentityFingerprint AuthenticationFingerprint ExtractionFingerprint RecognitionMobile AuthenticationOriented FastRotated BriefSecure Mobile AuthenticationSmartphones
We devised a mobile biometric-based authentication system only relying on local processing. Our Android open source solution explores the capability of current smartphones to acquire, process and match fingerprints using only its built-in hardware. Our architecture is specifically designed to run completely locally and autonomously, not requiring any cloud service, server, or permissioned access to fingerprint reader hardware. It involves three main stages, starting with the fingerprint acquisition using the smartphone camera, followed by a processing pipeline to obtain minutiae features and a final step for matching against other locally stored fingerprints, based on Oriented FAST and Rotated BRIEF (ORB) descriptors. We obtained a mean matching accuracy of 55%, with the highest value of 67% for thumb fingers. Our ability to capture and process a finger fingerprint in mere seconds using a smartphone makes this work usable in a wide range of scenarios, for instance, offline remote regions. This work is specifically designed to be a key building block for a self-sovereign identity solution and integrate with our permissionless blockchain for identity and key attestation.
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A fast parallel algorithm for thinning digital patterns
Tingwei Zhang, Ching Y. Suen · Communications of the ACM · 1984 · 2.7K citations · Full text
Fingerprint recognition using CNNs: fingerprint preprocessing
Qun Gao, Philippe Forster, K.R. Mobus et al. · 2002 · 24 citations