Medvedev, VGonçalves, NunoCruz, LeandroBrömme, ArslanBusch, ChristophDantcheva, AntitzaRaja, KiranRathgeb, ChristianUhl, Andreas2020-09-162020-09-162020978-3-88579-700-5https://dl.gi.de/handle/20.500.12116/34346Current trends in security of ID and travel documents require portable and efficient validation applications that rely on biometric recognition. Such tools can allow any authority and citizen to validate documents and authenticate citizens with no need of expensive and sometimes unavailable proprietary devices. In this work, we present a novel, compact and efficient approach of validating ID and travel documents for offline mobile applications. The approach employs the in-house biometric template that is extracted from the original portrait photo (either full frontal or token frontal), and then stored on the ID document with use of a machine readable code (MRC). The ID document can then be validated with a developed application on a mobile device with digital camera. The similarity score is estimated with use of an artificial neural network (ANN). Results show that we achieve validation accuracy up to 99.5% with corresponding false match rate = 0.0047 and false non-match rate = 0.00034.enDocument securitybiometric templateactive appearance modelartificial neural network.Text/Conference Paper1617-5468