//ez internal, mert csak a Benchmark keszithet uj Resultokat
internal Result(string signer, double frr, double far, double aer, ISignerModel model)
{
Signer = signer;
Frr = frr;
Far = far;
Aer = aer;
Model = model;
}
/// <inheritdoc/>
public double Test(ISignerModel signerModel, Signature signature)
{
// We are not doing real classification here, just reusing the previously calculated results
var model = (OptimalDtwSignerModel)signerModel;
var distance = model.SignatureDistanceFromTraining[signature.ID];
if (distance <= model.Threshold)
{
return(1);
}
else
{
return(0);
}
}
/// <inheridoc/>
public double Test(ISignerModel model, Signature signature)
{
var dtwModel = (DtwSignerModel)model;
var testSignature = signature.GetAggregateFeature(Features).ToArray();
var distances = new double[dtwModel.GenuineSignatures.Count];
for (int i = 0; i < dtwModel.GenuineSignatures.Count; i++)
{
distances[i] = DtwPy.Dtw(dtwModel.GenuineSignatures[i].Value, testSignature, DistanceFunction);
dtwModel.DistanceMatrix[signature.ID, dtwModel.GenuineSignatures[i].Key] = distances[i];
}
// returns value between 0 and 1, how confident is the decision about genuineness
// 1 -> conident genuine, 0 -> not confident genuine = confident forged
return(Math.Max(1 - (distances.Average() / dtwModel.Threshold) / 2, 0));
}
