SYSTEMS AND METHODS FOR BIOMETRIC AUTHENTICATION OF FINANCIAL TRANSACTIONSDate:2021-09-18
UNIVERSAL DIGITAL IDENTITY AUTHENTICATION SERVICE
In today's world cost optimization and better service are becoming the essential components ofthe retail supply chain. The thesis tries to contribute to the understanding of the RFIDtechnology in the retail industry. The basic concepts and the research contribution of the variousauthors are briefed in the theoretical framework made for a better understanding to the readers.After gained the relevant theoretical knowledge, the interviews were conducted with the RFIDexpert and some retailers. The empirical data collected from the interviews and surveys areprojected. With the empirical results and the relevant theoretical results, an analysis is madewhich explicitly gives the basis of implementation of RFID in the retail supply chain and itsassociated practical scenarios. Another outcome of the thesis is the result of the checkoutanalysis of the Willys retail store, and researchers try to show the potential benefit of adoptingthe RFID technology at item level at the point of sales, also cost estimation and savings areshown in the analysis. In a bird's eye view, this research thesis work is a contribution to theimplementation of RFID technology in the retail industry and its integration among the differententities of retail supply chain and improves the overall performance of supply chain and providea framework for RFID implementation for the case company.
The problem of fingerprint liveness detection has received an increasing attention in the last decade, as attested by the organisation of three editions of an international competition, named LivDet, dedicated to this challenge. LivDet editions and other works in the literature showed that the performance of current fingerprint liveness detection algorithms is not good enough to allow empowering a fingerprint verification system with a module aimed to distinguish alive from fake fingerprint images. However, recent developments have shown that texture-based features can provide promising solutions to this problem. In this study, a novel fingerprint liveness descriptor named binarised statistical image features (BSIFs) is adopted. Similarly to local binary pattern and local phase quantisation-based representations, BSIF encodes the local fingerprint texture into a feature vector by using a set of filters that, unlike other methods, are learnt from natural images. Extensive experiments with over 40,000 live and fake fingerprint images show that the authors' proposed method outperforms most of the state-of-the-art algorithms, allowing a step ahead to the real integration of fingerprint liveness detectors into verification systems.
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