Abstract
Current payment systems, including cash, credit cards, and UPI can be inconvenient for users, prompting the need for a more robust and user-friendly payment system. Biometric authentication methods like palm prints can enhance security and the user experience, but there is a lack of a reliable system that integrates palm print recognition with e-wallets to facilitate payments at participating merchants. Existing payment systems fail to provide a secure and convenient way to pay using palm prints, with challenges regarding the accuracy, reliability, and privacy of palm print recognition technology. By integrating palm print recognition technology with e-wallets, this work aims to meet the growing demand for a more advanced payment system that enhances the user experience while providing a secure way to make payments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Khan BUI, Olanrewaju RF, Baba AM, Langoo AA, Assad S (2017) A compendious study of online payment systems: past developments, present impact, and future considerations. Int J Adv Comput Sci Appl 8(5)
Bezovski Z (2016) The future of the mobile payment as electronic payment system. Eur J Bus Manage 8(8):127–132
Wu W, Elliott SJ, Lin S, Sun S, Tang Y (2020) Review of palm vein recognition. IET Biometrics 9(1):1–10
Ungureanu AS, Salahuddin S, Corcoran P (2020) Toward unconstrained palmprint recognition on consumer devices: a literature review. IEEE Access 8:86130–86148
Kumar A (2008) Incorporating cohort information for reliable palmprint authentication. In: 2008 Sixth Indian conference on computer vision, graphics & image processing. IEEE, pp 583–590
Shao, H, Zhong D, Du X (2019) Cross-domain palmprint recognition based on transfer convolutional autoencoder. In: 2019 IEEE international conference on image processing (ICIP) IEEE, pp 1153–1157
Bachay FM, Abdulameer MH (2022) Hybrid deep learning model based on autoencoder and CNN for palmprint authentication. Int J Int Eng Syst 15(3):41
Han WY, Lee JC (2012) Palm vein recognition using adaptive Gabor filter. Expert Syst Appl 39(18):13225–13234
Harivinod N, Shekar BH (2019) A bimodal biometric system using palmprint and face modality. In: Data analytics and learning: proceedings of DAL 2018. Springer, Singapore, pp 197–206
Zheng Q, Kumar A, Pan G (2015) Suspecting less and doing better: New insights on palmprint identification for faster and more accurate matching. IEEE Trans Inf Forensics Secur 11(3):633–641
Zhong D, Du X, Zhong K (2019) Decade progress of palmprint recognition: a brief survey. Neurocomputing 328:16–28
Baidong H, Yukun Z (2019) Research on quickpass payment terminal application system based on dynamic QR code. J Phys: Conf Ser 1168(3):032059 (IOP Publishing)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Saralaya, S., Kumar, P., Shehzad, M., Nihal, M., Nagure, P. (2024). Pay-by-Palm: A Contactless Payment System. In: Das, S., Saha, S., Coello Coello, C.A., Bansal, J.C. (eds) Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2023. Lecture Notes in Networks and Systems, vol 892. Springer, Singapore. https://doi.org/10.1007/978-981-99-9521-9_25
Download citation
DOI: https://doi.org/10.1007/978-981-99-9521-9_25
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-9520-2
Online ISBN: 978-981-99-9521-9
eBook Packages: EngineeringEngineering (R0)