Biometrics: Face Recognition
There is a growing interest in biometric authentication, for use in
such application areas as:
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National ID cards
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Airport security
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Surveillance
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Site access.
Biometrics that could potentially be used in these situations include:
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Fingerprints.
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Hand geometry.
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Iris.
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Retina.
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Gait.
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Voice.
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Signature.
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Vein patterns.
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Face.
Face recognition methods generally fall into four main categories:
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Neural networks.
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Feature analysis.
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Graph matching.
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Information theory.
Face recognition has a number of advantages over some of the other biometrics
used. Firstly, it is non-intrusive. Whereas many biometrics
require the subjects co-operation and awareness in order to perform an
identification or verification, such as looking into an eye scanner or
placing their hand on a fingerprint reader, face recognition could be performed
even without the subject's knowledge. Secondly, the biometric data
used to perform recognition is in a format that is readable and understood
by humans. This means that a potential face recognition system can
always be backed up and verified by a human. For example, supposing
a person was falsely denied access to a site by a face recognition system.
That decision could easily be corrected by a security guard that would
compare the subject's face with the stored image, whereas this would not
be possible with other biometrics such as iris. Other advantages
are that there is no association with crime as with fingerprints (few people
would object to looking at a camera) and many existing systems already
store face images (such as police mug shots).
The term face recognition encompasses three main procedures. The
preliminary step of face detection (which may include some feature localisation)
is often necessary if no manual (human) intervention is to be used.
Many methods have been used to accomplish this, including template based
techniques, motion detection, skin tone segmentation, principal component
analysis and classification by neural networks. All of which present
the difficult task of characterizing “non-face” images. Also, many
of the algorithms currently available are only applicable to specific situations:
assumptions are made regarding the orientation and size of the face in
the image, lighting conditions, background and subject's co-operation.
The next procedure is verification. This describes the process by
which two face images are compared, producing a result to indicate if the
two images are of the same person. Another (often more difficult)
procedure is identification. This requires a probe image, for which
a matching image is searched for in a database of known people, thus identifying
the probe image as a specific person.