A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science, School of Computer Science and Applied Mathematics. May 2017. / Biometric features have been widely implemented to be utilized for forensic and civil applications. Amongst many different kinds of biometric characteristics, the fingerprint is globally accepted and remains the mostly used biometric characteristic by commercial and industrial societies due to its easy acquisition, uniqueness, stability and reliability.
There are currently various effective solutions available, however the fingerprint identification is still not considered a fully solved problem mainly due to accuracy and computational time requirements. Although many of the fingerprint recognition systems based on minutiae provide good accuracy, the systems with very large databases require fast and real time comparison of fingerprints, they often either fail to meet the high performance speed requirements or compromise the accuracy.
For fingerprint matching that involves databases containing millions of fingerprints, real time identification can only be obtained through the implementation of optimal algorithms that may utilize the given hardware as robustly and efficiently as possible. There are currently no known distributed database and computing framework available that deal with real time solution for fingerprint recognition problem involving databases containing as many as sixty million fingerprints, the size which is close to the size of the South African population.
This research proposal intends to serve two main purposes: 1) exploit and scale the best known minutiae matching algorithm for a minimum of sixty million fingerprints; and 2) design a framework for distributed database to deal with large fingerprint databases based on the results obtained in the former item. / GR2018
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/23747 |
| Date | January 2017 |
| Creators | Muhammad, Atif |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | Online resource (vi, 63 pages), application/pdf |
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