2. Fingerprints
A fingerprint is a series of dark lines that represent the high
portions and valleys of friction ridge skin.
This technology uses the fact that no two people have
identical fingerprints.
Fingerprint recognition devices create an image of these
prints and compare them with fingerprints that are already on
file on the system.
A variety of sensor types-optical, thermal, capacitive and
ultrasound- are used for collecting the digital image of a
fingerprint. Optical scanners take a picture of the image and
are the most common hardware used. Other devices use pixel
value, high frequency devices that detect the change in light
reflection or the difference in temperature to produce an
image.
3.
4. Face Recognition
Facial recognition software uses the ability to recognize a
face and then pinpoint various features of the face. Every
face has distinguishable landmarks, peaks and valleys, that
make up facial features. These are measured by the
software.
Face recognition works by using a computer to analyze an
individual’s facial structure. The points measured include
distances between key characteristics such as eyes, nose
and mouth, angles of key features such as the jaw and
forehead, and lengths of various portions of the face.
With this information, the program creates a unique
template, called a face print, using all of the numerical
data. This face print may then be compared to a database
of facial images to identify the subject
5.
6. Speaker Recognition
• This is a type of biometric input that uses an individual’s
voice for recognition purposes.
• It comes in two forms: identification and verification
• Speech identification recognizes who is speaking by using
the specific information included in speech waves to verify
identities being claimed by people accessing systems .
• Speech verification utilizes a computer program to
anticipate certain specific patterns of speech and then
verify that those patterns in a voice recording or live person
speaking.
• Text dependent systems requires predetermined utterances
while text independent do not
7.
8. Iris Recognition
• The iris is a muscle in the eye that controls the size of
the pupil
• This system is able to localise the circular iris and the
pupil region excluding other regions around the eyes.
It then analyzes the random structure of the iris
• The iris is unique because there is a certain degree of
randomness in their structure
• First, a black-and-white video camera zooms in on
the iris and records a sharp image of it. The iris is lit
by a low-level light to aid the camera in focusing.
9.
10. Hand and Finger Geometry
• Hands and fingers are unique but not as unique as other
traits (fingerprints, irises). Because of this they are used
to authenticate users rather than identify them.
• Biometric hand recognition systems measure and analyze
the structure, shape and proportions of the hand such as
length, width and thickness of hand, fingers and joints;
creases and ridges on the skin’s surface.
• The user places the palm of his or her hand on the
reader's surface and aligns it with the guidance pegs on
the device. The device captures the image using a camera
and light and checks its database for verification of the
user.
11.
12. Signature Verification
• This analyzes the way a person signs their name.
Signature characteristics are absolutely unique to
an individual and virtually impossible to
duplicate.
• Features analyzed include speed, acceleration,
deceleration, stroke sequencing and length, pen
pressure and signature shape.
• In signature verification the signature in question
is scrutinized and compared against a reference
signature kept on file to determine the
signature's genuineness.