Hologram Detection: Securing ID Verification
Blog post from Didit
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Holograms in passports, driver’s licenses, and other identity documents use diffractive optical structures, microtext, shifting patterns, and hidden images to deter forgery, but increasingly accessible technologies such as e-beam lithography, digital embossing, and film transfer have enabled more convincing counterfeits. Because visual inspection alone may not identify sophisticated fakes, modern authentication methods examine holograms’ spectral signatures, microscopic structures, diffraction patterns, and similarity to databases of genuine examples. Machine-learning systems trained on authentic and counterfeit samples can identify subtle anomalies and, alongside spectral analysis, may achieve detection rates above 99% in controlled settings. Didit presents its identity-verification platform as a layered solution that combines automated hologram analysis, high-resolution mobile image capture, microscopic feature detection, reference databases, and broader KYC/AML checks such as data extraction, liveness detection, and screening.
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