1、The Role of AI in Fingerprint Recognition:From Image Enhancement to Feature Extraction Different Features for Different Domains(Civil&Criminal)International Face and Fingerprint Performance Conference(IFPC)2025Evaldas Borcovas,Head of Biometrics Research,Neurotechnology April NNeurotechnology is est
2、ablishedin LThe companys headquarters are located in VBiometricsNeurotechnology is like a small private university for researcherswho want to push technology Compliant and evaluated in most of the Fingerprint recognition pipelineData acquisition Quality assuranceEnrolmentVerification/IdentificationR
3、esult AI is transforming traditional fingerprint recognitionProblems which could not be solved before AI,now can be solvedData acquisitionClassic image processingClassic fingerprint featuresAI data generationAI fingerprint enhancementAI fingerprint Fingerprint Data ACollecting data-civil use Generat
4、ing data plain Generating data-rolled Collecting data-criminal use Generating data latent Fingerprint Enhancement Hard fingerprint Fingerprint Enhancement Classic Fingerprint Enhancement Classic Fingerprint Enhancement AI Fingerprint Enhancement AI Fingerprint Enhancement-Classic vs AI Rolled genuin
5、e match with classic Rolled genuine match with AI Fingerprint Recognition FFingerprint recognition Fast search features level 1 Classic recognition features level 2 Advanced recognition features level 2&3 ELFT 0122 with level 1&2&3 Subset from NIST SD 302 BComparison of different features-civil use
6、caseLevel 1 featuresLevel 2 featuresLevel 1&2 featuresLevel 2&3 Subset from NIST SD 302 IComparison of different features-law enforcement caseLevel 1 featuresLevel 2 featuresLevel 1&2 featuresLevel 2&3 Subset from NIST SD 302 IEFS usage-law enforcement use cas