Okokpujie, Kennedy O. and Noma-Osaghae, Etinosa and John, S. N. and Etta, Joy (2018) Comparative Analysis of Fingerprint Preprocessing Algorithms for Electronic Voting Processes. In: Lecture Notes in Electrical Engineering. Lecture Notes in Electrical Engineering book series (LNEE, volume 450), 450 . Springer, Singapore, Singapore. ISBN 978-981-10-6454-8 (In Press)
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Abstract
Fingerprints have been used for a long time as a very adequate method of distinguishing people. Matching fingerprints can be very difficult without a good algorithm for the scanners. Complexities especially during the verification phase can arise from problems with the algorithm scanners use. In elections and other forms of voting, security and proof of individuality remain some of the biggest obstacles to be surmounted. This project proposes an ideal algorithm which could solve these challenges. The Zhan-Suen Thinning Algorithm and the Guo–Hall Parallel Thinning Algorithm were compared using standard parameters from the perspective of fingerprint technology and electoral requirements to deduce the better algorithm. MATLAB® was used for the comparative performance analysis of the two algorithms. The time taken to complete iterations, quality of output produced and reliability were the parameters used to carry out the comparative performance analysis of the two algorithms. The better algorithm, Guo–Hall’s was recommended for implementation on e-voting systems. Guo-Hall’s algorithm is very effective and has the capacity to curb electoral fraud when adopted in e-voting process.
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | Thinning Authentication Enrollment Verification |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Dr. Etinosa Noma-Osaghae |
| Date Deposited: | 04 Jan 2018 10:32 |
| Last Modified: | 04 Jan 2018 10:32 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/9911 |
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