This thesis deals with the issue of reconstruction of damaged fingerprints using artificial neural networks. At first, the fingerprint structure is analyzed, after that, the methods that can be used to improve fingerprint quality are described. An introduction to neural networks is given for understanding the basics of artificial neural networks. After choosing the right architecture for the neural networks, the process of its learning is described. A simple graphic user interface was created for this application, which is able to reconstruct synthetic fingerprints damaged by various warts. Another neural net can detect the location of wart. Tests have proven an increase in the quality of fingerprint by 43,5 % in the dataset with ten inserted warts on each fingerprint. The matching score was increased by 6,5 % on this particular dataset.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:417213 |
| Date | January 2020 |
| Creators | Halinár, Michael |
| Contributors | Tinka, Jan, Kanich, Ondřej |
| Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
| Source Sets | Czech ETDs |
| Language | Slovak |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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