The key to ensuring security in fingerprint systems is to consistently capture a significant number of characteristic features within the surface of the human finger.

Given a sufficient number of such features, a high-quality system quickly and accurately determines the probability of whether a submitted print represents the correct person or not.

The larger the sensor, the greater the number of features likely to be captured. The images below illustrate this direct correlation between sensor size and the number of features likely to be captured.


In this example a feature rich finger is used. The algorithm used is a high quality image processing and minutiae extraction algorithm. The sensors from 148 mm2 and up will with a very high probability capture enough features for the algorithm to be able to securely determine the authenticity of a finger presented to the sensor system. 

The NEXT sensor in this example captures 18 minutiae points, a print which if enrolled will be highly robust for real life usage. Experts are aware that there is a difference between biometrics for demo or the classroom and biometrics in a commercial application. In real life, disturbing factors including the following will happen: skewed placements, wet, dirty, worn or dry fingers, cuts in the finger, dirt on the sensor area. Having a high quality sensor with a large area adds an important buffer for tolerating all of these challenges and still reliably authenticate an individual.