Fingerprint Technology Overview

Fingerprint Technology Overview

29/11/2020 11:41:21 PM | 2272

Fingerprint Technology Overview

The unique nature of a fingerprint makes it ideal for use in automated recognition systems. A fingerprint is made of a series of ridges and grooves. Once a fingerprint is captured the system locates the minutia points. These minutia points occur where the lines of the ridges begin, end, branch off and merge with other ridge lines. These points are then mapped and a line is drawn between each point. This creates a map of how each point relates to the other points. The map is then stored as a data stream called a minutia template in a database for future comparison with other presented fingerprints. It is important to note that during the entire process no fingerprint images are stored on the system and a fingerprint image cannot be recreated from the minutia template.

MinutiaCapture

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.



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