Fingerprint Biometrics

What is Biometrics?

Biometrics are automated methods of recognizing a person based on a physiological or behavioral characteristic. Among the features measured are face, fingerprints, hand geometry, handwriting, iris, retinal, vein, and voice. Biometric data are separate and distinct from personal information. Biometric templates cannot be reverse-engineered to recreate personal information and they cannot be stolen and used to access personal information.

Using a unique, physical attribute of your body, such as your fingerprint or iris, to effortlessly identify and verify that you are who you claim to be, is the best and easiest solution in the market today. That is the simple truth and power of Biometrics Technology today. Although biometric technology has been around for many years, modern advances in this emerging technology, coupled with big reductions in cost, now make biometrics readily available and affordable to consumers, small business owner, larger corporations and public sector agencies alike.

Fingerprint recognition technology

The most famous application of fingerprint recognition technology is in criminology. However, nowadays, automatic fingerprint matching is becoming increasingly popular in systems which control access to physical locations (such as doors and entry gates), computer/network resources or bank accounts, or which register employee attendance time in enterprises.

Straight forward matching of the to-be-identified fingerprint pattern against many already known fingerprint patterns would not serve well, due to the high sensitivity to errors in capturing fingerprints (e.g. due to rough fingers, damaged fingerprint areas or the way a finger is placed on different areas of a fingerprint scanner window that can result in different orientation or deformation of the fingerprint during the scanning procedure). A more advanced solution to this problem is to extract features of so called minutiae points (points where the tiny ridges and capillary lines in a fingerprint have branches or ends) from the fingerprint image, and check matching between these sets of very specific fingerprint features.

The extraction and comparison of minutiae points requires sophisticated algorithms for reliable processing of the fingerprint image, which includes eliminating visual noise from the image, extracting minutiae and determining, rotation and translation of the fingerprint. At the same time, the algorithms must be as fast as possible for comfortable use in applications with a large number of users.

Many of these applications can run on a PC, however some applications require that the system be implemented on low cost, compact and/or mobile embedded devices such as doors, gates, handheld computers, cell phones etc.). For developers who intend to implement the fingerprint recognition algorithm into a microchip, compactness of algorithm and small size of required memory may also be important.