Neural Biometric
Neural biometric is a revolutionary new biometric modality that mimics human cognition - how the human brain naturally and instinctively recognises people.
Developed by research scientists from aiThenticate Computervision Labs[1] at the University of Johannesburg (South Africa)[2], the technology (code-named 'aiDX') converts a digital image of a subject captured on any optimetric device (mobile phone, tablet computer, notebook computer, desktop computer, webcam, ATM, kiosk...) into a complex digital representation of the brain's semantic memory (a subject's own 'Digital aiD') that represents an individual's own unique idiotype.
A subject's own unique Digital aiD is mathematically expressed as a complex, irreversible, binary crypto hash.
Whereas conventional biometrics (fingerprint, facial recognition, voice recognition, retinal and iris scans...) employ a simple analytic approach to join key characteristics (minutiae, facial landmarks...) to form a flat geometric pattern in 2D space, a neural biometric on the other hand interprets the full range of physiognomic features and characteristics visible in the human face in 3D space.
Typically, a neural biometric generates approximately 29,182,858,167,028,700,000,000,000,000,000,000 unique possibilities, making it suitable for large population groups.
In collaboration with neuroscientists from the University of Johannesburg (South Africa), researchers at aiThenticate Computervision Labs have furthermore been able to discover exactly how the brain's semantic memory of a particular subject is reinforced through repeated exposure to the subject - using deep science, researchers were able to develop algorithms that equally strengthen and make the digital identity (or 'Digital aiD') of a subject more reliable and more robust with increased use.
As a neural biometric, the technology has been shown to be highly resilient to feature drift caused by ageing, weight loss/gain, ill-health... over time.
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Neural Biometric[edit]
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