The Implementation of Touchless Fingerprint Accreditation System to Prevent Disenfranchisement in Global Election Using Machine Learning
Abstract
Full Text:
PDFReferences
Tony P. A and Adebimpe O.E. (2018); the impact of ICT in the conduct of election in Nigeria; American journal of computer science and technology.
http://www.vangurardngr.com
Prasanna V. Serge B. David K. (2011); Wet fingerprint recognition; Challenges and opportunities; University of California, San Diego.
Tanjaru M. and Mijanur R. (2018); Vulnerabilities of fingerprint authentication systems and their securities; International Journals of computer science and information security.
Javier G., Gunnar B. and Laurent B (2017); Full 3D Touchless fingerprint recognition sensor, database and baseline performance. European commission, DG joint Research center, Italy.
Chulhan Lee, Sanghoon Lee and Jaihie Kin (2006); A study of Touchless fingerprint recognition system. Yonsei Univeristy, Korea.
T. Matsumoto, H. Matsumoto, K. Yamada, and S. Hoshino, ”Impact of artificial ”gummy” fingers on fingerprint systems”, In Proceedings of SPIE Vol. Num.4677, Jan 2002.
Oleka C. (2018); the application of iris scan to improve the accuracy of existing face recognition system using computer vision and machine learning. Enugu state university of science and technology (Esut), Nigeria.
Muja, M., and D. G. Lowe (2009). "Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration." International Conference on Computer Vision Theory and Application; VISAPP.
http://www.Mathworks 2018a/documentations.
DOI: https://doi.org/10.23956/ijarcsse.v9i7.1044
Refbacks
- There are currently no refbacks.