Machine Authentication of Security Documents

This paper presents a pioneering effort towards machine authentication of security documents like bank cheques, legal deeds, certificates, etc. that fall under the same class as far as security is concerned. The proposed method first computationally extracts the security features from the document images and then the notion of dasiagenuinepsila vs. dasiaduplicatepsila is defined in the feature space. Bank cheques are taken as a reference for conducting the present experiment. Support Vector Machines (SVMs) and neural networks (NN) are involved to verify authenticity of these cheques. Results on a test dataset of 200 samples show that the proposed approach achieves about 98% accuracy for discriminating duplicate cheques from genuine ones. This strongly attests the viability of involving machine in authenticating security documents.