EURASIP Journal on Information Security

Table 2 The classification error of the supervised binary classifier (in %)^a

From: Mobile authentication of copy detection patterns

Setup on	Originals	Fakes #1	Fakes #1	Fakes #2	Fakes # 2
Setup on	(\(P_{miss}\))	White (\(P_{fa}\))	Gray (\(P_{fa}\))	White (\(P_{fa}\))	Gray (\(P_{fa}\))
Fakes #1 white	0	0	0.14	0	0
Fakes #1 gray	0	0	0	0	0
Fakes #2 white	0	99.43	100	0	0
Fakes # 2 gray	0	99.29	99.86	0	0

^aPresented binary classification is close to the multi-class classification scenario with 2 classes considered in Section 3.2.1. The difference in the obtained results is related to the presence of all types of fakes during the training in case of multi-class setup and randomly chosen training data

Back to article page