This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is an analyzer. It can only be used on analysis blocks.

Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.

Group: main

Endpoint Name Data Format Nature
score system/float/1 Input
class system/boolean/1 Input

Analyzers may produce any number of results. Once experiments using this analyzer are done, you may display the results or filter experiments using criteria based on them.

Name Type
eer float32
number_of_negatives int32
scores_distribution plot/bar/1
number_of_positives int32
roc plot/isoroc/1
threshold float32

The code for this algorithm in Python
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An algorithm that implements simple metrics for the LivDet2013 Competition

Specifically, it returns:

  • eer: the equal error rate (EER) on the test set.
  • number_of_positives: the number of positive (genuine) trials on the test set
  • number_of_negatives: the number of negative (spoof) trials on the test set
  • threshold: the threshold at the equal error rate on the test set
  • roc: the receiver operating characteristic (ROC) curve on the test set according to the biometrics standard ISO/IEC 19795-1:2006(E)

This implementation relies on the 'measure' package from the Bob library.

Experiments

Updated Name Databases/Protocols Analyzers
anjos/anjos/livdet-lda/1/livdet-2013-biometrika-test livdet2013/1@Biometrika anjos/livdet_analysis/1

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

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