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Finger Vein\Print Technology Overview

Finger Vein\Print technology combines two highly accurate and easy to use biometric technologies. The user presents their finger to the reader and the fingerprint and finger vein are read concurrently as a single operation.

Fusion

Accuracy

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The multi-modal finger vein\print technology identifies candidates that would have been rejected by using just fingerprint only or just finger vein only technology. Finger Vein\Print false rejection rate (FRR) is 10 times lower than Fingerprint and more than 50 times lower then Finger Vein.

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Fingerprint biometric data is acquired using an optical sensor by total reflection using visible light. Finger vein biometric data is captured by infra-red illumination and reflection by direct view using near infra-red light.

Finger vein data resides below the skin and is a highly effective anti-spoofing technology.

Vein

When acquiring a fingerprint and finger vein it is critical that the correct part of the finger is available to acquire the fingerprint and the finger vein. The sensor hardware is designed that during enrollment the enrollee’s fingertip and finger base must make contact with the top and bottom of MSO FVP. For identification and verification only the fingertip must make contact with the top of the MSO FVP.

Review the Fingerprint Technology Overview for more information on fingerprint technology.

Differences between Identification & Authentication
Identification (also known as 1:Many, 1:X or One to Many)
Using specialised indexing techniques a sample is effectively matched against all templates in the database. In specialised high end systems a sample can be matched in against hundreds of thousands

Put simply, a person does not have to provide any input other than their biometric.

Authentication (also known as Verification, 1:1 or One to One)
The sample is matched against one pre-selected template.

Put simply, a person swipes a card or enters a user code to select a biometric template to match against.

Measuring biometric effectiveness
There are 2 commonly used gauges for measuring the effectiveness of biometrics matching technology.

1. False Rejection Rate (FRR) as known as False Non-Match Rate (FNMR)
FRR is a value that measures the percentage of times a biometric sample is matched against a single or multiple biometric templates where a biometric template exists but the likeness between the sample and template is below the decision threshold setting so no match occurs.

Put simply, it’s the number of times people do not get identified when they should be identified.

2. False Accept Rate (FAR) also know as False Match Rate (FMR)
FAR is a value that measures the percentage of times a biometric sample is matched against a single or multiple biometric templates where a biometric template does not exist but the likeness between the sample and template is above the decision threshold setting so a match incorrectly occurs.

Put simply, it’s the number of times people get identified when they should not be identified.