In all of them, given raw data as input it does the following steps:
Sub-pipeline 1:\n
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Training background model. Some biometric algorithms demands the training of background model, for instance, PCA/LDA matrix or a Neural networks. This sub-pipeline handles that and it consists of 3 steps:
Creation of biometric references: This is a standard step in a biometric pipelines.
Given a set of samples of one identity, create a biometric reference (a.k.a template) for sub identity. This sub-pipeline handles that in 3 steps and they are the following:
Note that this sub-pipeline depends on the previous one
Sub-pipeline 3:\n
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Probing: This is another standard step in biometric pipelines. Given one sample and one biometric reference, computes a score. Such score has different meanings depending on the scoring method your biometric algorithm uses. It's out of scope to explain in a help message to explain what scoring is for different biometric algorithms.