Skip to main navigation Skip to search Skip to main content

Evaluation of Local Binary Pattern Algorithm for User Authentication with Face Biometric

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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world of computer security and user authentication, the username/password standard is becoming increasingly outdated.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.
Original languageEnglish
Title of host publication19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020
DOIs
StatePublished - 2020

Fingerprint

Dive into the research topics of 'Evaluation of Local Binary Pattern Algorithm for User Authentication with Face Biometric'. Together they form a unique fingerprint.

Cite this