Pattern recognition is the scientific discipline whose
goal is the classification of objects into a number of categories or classes.
Depending on the application, these objects can be images or signal wave forms
or any type of measurements that need to be classified. We will refer to these
objects using the generic term patterns. Pattern recognition has a long history, but before the
1960s it was mostly the output of theoretical research in the area of
statistics. As with everything else, the advent of computers increased the
demand for practical applications of pattern recognition,
which in turn set new demands for further theoretical developments. As our
society evolves from the industrial to its postindustrial phase, automation in
industrial production and the need for information handling and retrieval are
becoming increasingly important. This trend has pushed pattern recognition to the high edge of today's
engineering applications and research. Pattern recognition is an integral part of most machine
intelligence systems built
for decision making.
The
knowledge of finding out the identity of a distinct entity based on the
physical, behavioral or chemical characteristics of a person is called Biometrics. It originates from
two words bios (means life) and Merton (means measure). The biometrics is mostly used for employing the
identity management in wide-ranging situations in which precise individual
identification is fundamental.
Some of the biometric applications are employed in
situations where the networks are being shared between the users, in
electronically business deals (such as e-shopping and ATM stations) and in any
other commercial transactions.
The identity identification may be essential for a variety of
factors though the major goal, in most programs, will be to avert invaders from
penetrating to the covered property. Three ways of creating a person’s identity
comprise the following mechanism
No comments:
Post a Comment