Fingerprint Technology

A brief introduction

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Among all the biometric technologies, fingerprint-based identification is the oldest method which has been successfully used in numerous applications.

Introduction to Fingerprint Patterns

The uniqueness of fingerprint has long been recognized as an unquestionable identification of an individual. The uniqueness of fingerprints can generally be classified into two main categories: Global Ridge Patterns and the Local Ridge Patterns.

The Global Ridge Patterns have been widely use by the Law Enforcement, AFIS (Automated Fingerprint Identification System) for broad classifications. There are four main classifications:

a) Arch b) Left Loop c) Right Loop d) Whorl



The characteristics of the Local Ridge Patterns are also known as minutiae or points of identification, are unique to individual fingerprint. There are used for fingerprint identification by all AFIS in law-enforcement agencies. The Local Ridge Patterns include ridge ending, bifurcation, short ridge, dot and island.

Fingerprint recognition

Fingerprint-based identification can be placed into two categories: minutiae-based matching (analysing the local ridge patterns) and global pattern matching (analysing the global ridge patterns). Currently the computer aided fingerprint recognition is using the minutiae-based matching.

The uniqueness of a fingerprint can be determined by the pattern of the ridges and the valleys a fingerprint is made of. A complete fingerprint consists of about 100 minutiae points in average. The measured fingerprint-area consists in average of about 30-60 minutiae points depending on the finger and on the sensor area.



These minutiae points are represented by a cloud of dots in a coordinate system. They are stored together with the angle of the tangent of a local minutiae point in a fingerprint-code or directly in a reference template. A template can consist of more than one fingerprint-code to expand the amount of information and to expand the enrolled fingerprint area. In general this leads to a higher template quality and therefore to a higher similarity value of the template and the sample.

Fingerprint Sensor

The fingerprint scanner is the input device to read the individual fingerprint image for authentication. A good and reliable fingerprint scanner is important to make the application system more robust and secure.

The whole process

The stages of the minutiae detection and matching process are shown in the diagram below: