null
(Ed.)
In the ever-changing world of computer security
and user authentication, the username/password standard is
becoming increasingly outdated. Using the same username
and password across multiple accounts and websites leaves a
user open to vulnerabilities, and the need to remember
multiple usernames and passwords feels very unnecessary in
the current digital age. Authentication methods of the future
need to be reliable and fast, while maintaining the ability to
provide secure access. Augmenting traditional username-password
standard with face biometric is proposed in the
literature to enhance the user authentication. However, this
technique still needs an extensive evaluation study to show
how reliable and effective it will be under different settings.
Local Binary Pattern (LBP) is a discrete yet powerful
texture classification scheme, which works particularly well
with image classification for facial recognition. The system
proposed here strives to examine and test various LBP
configurations to determine their image classification
accuracy. The most favorable configurations of LBP should
be examined as a potential way to augment the current
username and password standard by increasing their security
with facial biometrics.
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