Graphical gesture-based authentication for non-contact access control

Shaun Van Wyk, Dustin Van Der Haar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Access control is regarded as absolutely crucial in any environment, especially in home and work environments where sensitive resources are accessed. In this paper, we propose a non-contact, gesture-based authentication alternative to password authentication. The solution focuses on capturing specific graphical information, in the form of patterns drawn in the air, as a means of authentication. The solution presents a model, validated by a prototype in order to assess the solution against various metrics. This solution has achieved promising performance results, related to the false acceptance rate (FAR), false rejection rate (FRR), failure to enroll rate (FTER) and failure to acquire rate (FTAR), showing the ability to potentially compete with existing biometric systems. Furthermore, the solution succeeds in investigating a solution that is more difficult to subvert through the integration of various parameters.

Original languageEnglish
Title of host publication2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, PRASA-RobMech 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509033355
DOIs
Publication statusPublished - 10 Jan 2017
Event2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, PRASA-RobMech 2016 - Stellenbosch, South Africa
Duration: 30 Nov 20162 Dec 2016

Publication series

Name2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, PRASA-RobMech 2016

Conference

Conference2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, PRASA-RobMech 2016
Country/TerritorySouth Africa
CityStellenbosch
Period30/11/162/12/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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