English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this work, the authors propose a new biometric authentication system on mobile devices, enhancing security at these terminals and preserving user privacy. The proposed system uses a method of extracting strong features from minutiae with refinement of the method with regard to the further elimination of false minutiae by the calculation of geometric information (orientations and distances between minutiae) to obtain true terminations and stronger bifurcations facilitating the recognition of individuals. A series of tests carried out using a recognition and authentication application allowed us to achieve a false rejection rate of 13.81% and a false acceptance rate of almost zero (0.021%). The authors also propose a security model using hash functions and a random number to make the recognition system revocable, more difficult to compromise and thus reducing the risk of usurpation.

Biometric Authentication Methods on Mobile Platforms: An Introduction to Fingerprint Strong Feature Extraction