signalspot.com

Humans have traditionally
identified
each other by their
appearance, by
the sound and
content of their speech,
and by context. By using
these parts of the body
and with the help of
?BIOMETRICS? many
security systems are being
developed. We have many
security
systems but failed to
identify the terrorist
hijackers who crashed the
aero
planes into buildings on
?September 11?though
they were in FBI “watch
lists,? To
over come some of the
defaults of these security
systems we have ?THE
IRIS
SECURITY SYSTEM?.

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DIMENSIONALITY
REDUCTION IN PCA FOR
FACE RECOGNITION
Training set of face images
which is a subset of JNTU
Face Database ABSTRACT
Face recognition is an
advanced statistical
technology in computer
systems that can assist
recognition of human faces
using principal component
analysis (PCA) by
comparing the given facial
characteristics with the
already available data
(faces). Human faces are
normally upright so they
can be treated as 2-D
images rather than 3-D.
The 2-D facial image can be
converted into a 1-D
vector of pixels and
projected into the principal
components of the feature
space called the
eigenspace projection,
which is calculated from the
eigenvectors of the
covariance matrix derived
from a set of facial images.
The projections

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AUTOMATIC HUMAN FACE
RECOGNITION USING
RADON TRANSFORM Fig.1
Radon transform of the
image ABSTRACT This
paper presents a new
technique for face
recognition using Radon
transform. The technique
captures the facial
features from different
directions. Proposed
method which is robust to
zero mean additive white
noise derives local and
directional information of
the face images. The
technique acts as low pass
filter, enhancing low
frequency components
useful in face recognition
which improves the
recognition rate. The
images are classified by
using minimum distance 1
classifier. The feasibility of
Radon transform based
model has been
successfully tested using
ORL database. The
effectiveness of the
algorithm is shown in terms
of absolute performance
and compared

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