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[4.0.4] - Release Notes

This release updates SelphID SDK with new features related to Facial Liveness evaluation processes. This release is recommended for customers who are employing Liveness Evaluation and require major feasibility and usage in their projects.

New facial passive liveness engine implemented

A new facial passive liveness for facial spoof detection related to evaluate the liveness from a single image is integrated in this release. This new facial passive liveness engine improves:

  • Security
  • Usability

Evaluation set

A test set has been used that contains experiments focused on Facial Spoof Detection contemplating the following scenarios:

  • Genuines
  • Paper
  • Phone
  • Tablet
  • Screen
  • Screen 4K
  • Photo
  • Paper mask
  • Latex mask

Population: 382K samples The experiments carried out are based on the different circumstances described in the evaluations of ISO 30107.

Metrics

To carry out the study on the operation of the new SDK, the following metrics have been taken into account according to ISO 30107:

  • FTA: It is the proportion of samples that could not be acquired because the expected biometric characteristic was not detected compared to the total number of attempts made.
  • APCER: It is the proportion of Presentation Attacks (Attacks) incorrectly classified as genuine against the total number of attempts made in a specific scenario.
  • BPCER: It is the ratio of Bona Fide Presentations (Genuine) incorrectly classified as Presentation Attacks against the total number of attempts made in a specific scenario.