Introduction
to Fingerprints
The
uniqueness and permanence of the fingerprints are very well-know.
Archaeological artifacts prove that fingerprints were already
used by the ancient Assyrians and Chinese as a form of identification
of a person. The first scientific studies on fingerprints
date from the late sixteen century, but the fundamentals of
modern fingerprint identification methods were provided at
the end of nineteenth century. The studies of Sir F. Galton
and E. Henry led to formally accept fingerprints as valid
signs of identity by law enforcement agencies.
The first Automated Fingerprint Identification Systems (AFIS)
were developed in the 1950s by the F.B.I. (Federal Bureau
of Investigation) in cooperation with the National Bureau
of Standards, the Cornell Aeronautical Laboratory, e Rockwell
International Corp. Ten years later other AFISs were developed
by NEC Technologies Inc. ( Tokyo
), Printrack Inc. ( Anaheim
, California
), and Morpho System (Paris).
Fingerprint recognition is nowadays the basic task of the
Integrated Automated Fingerprint Identification Service (IAFIS)
of the most famous police agencies. Ten-print based identification
and latent fingerprint recognition are the two main concerns
of an IAFIS. In the former, the system should identify a person
by the whole sequence of his/her ten fingerprints, in the
latter it has to identify a person through a latent fingerprint
found on a crime scene. Technology advances in the 1980s in
the areas of personal computing and optical scanners triggered
non-forensic applications of fingerprint recognition methods.
The enormous interest roused by electronic commerce on Internet
and, more in general, by the need of reliable techniques for
authenticating the identity of a living person in a broad
range of applications has greatly intensified the research
efforts towards the development of low cost small-size fingerprint-based
biometric systems.
Fingerprint
Anatomy
A
fingerprint is the representation of the epidermis of a finger.
At a macroscopic analysis, a fingerprint is composed of a
set of ridge lines
which often flow
parallel and sometimes produce local macro-singularities called
whorl ,
loop
and delta .
The
number of cores and deltas in a single fingerprint is regulated
in nature by some stringent rules; fingerprints are usually
partitioned into five main classes ( arch,
tented arch, left loop, right loop, whorl )
according to their macro-singularities.
The
ridge-line flow can be effectively described by a structure
called directional
map (or directional
image) which is a discrete matrix whose elements denote the
orientation of the tangent to the ridge lines. Analogously,
the ridge line density can be synthesized by using a density
map.
At
a finer analysis other very important features can be discovered
in the fingerprint patterns. These micro-singularities, called
minutiae
or Galton characteristics, are essentially determined by the
termination
or the bifurcation
of the ridge lines.
Minutiae play a primary role for fingerprint matching, since
most of the algorithms rely on the coincidence of minutiae
to state whether two impressions are of the same finger or
not. Minutiae matching, which is essentially a point pattern
matching problem, constitutes the basis of most of the automatic
algorithms for fingerprint comparison.
Fingerprint
acquisition
The
oldest and most known fingerprint acquisition technique is
the "ink technique", that is, pressing the finger
against a card after spreading the finger skin with ink; this
technique is nowadays still largely used by the police in
AFIS. The cards are converted into digital form by means of
scanners identical to those normally employed for general
purpose paper documents. The default resolution is 500 dpi.
This technique can produce images including regions which
miss some information, due to excessive inkiness or to ink
deficiency, and is obviously limited to forensic applications.
The Frustrated Total Internal Reflection (FTIR) is the most
used and mature live-scan sensing technique. The finger is
illuminated from one side of a glass prism with a LED, while
the other side transmits the image through a lens to a CDD/CMOS
sensing element which converts light into digital information.
The lack of reflection caused by the presence of water particles
where the ridges touches the prism allows ridges to be discriminated
from valleys.
Back
to top
|
