|
|
Reconstruction of Damaged Parts of Fingerprint Image Using Neural Nets
Halinár, Michael ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
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.
|
|
|
Synthetic Fingerprint Generation from Biometric Template
Šuba, Adam ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
The goal of this master thesis is to design and implement an approach for synthetic fingerprint generation from a biometric template. The thesis bases the solution on an existing fingerprint generator called SyFDaS developed at the Brno University of Technology, Faculty of Information Technology. Individual components of the generator had to be modified and automized to suit better the task of generating from a template. The end product enables the user to create a fingerprint without any intervention just by importing a template. The evaluation in this thesis presents results obtained by comparing the synthetic and original fingerprints using the VeriFinger algorithm. Entirely automatically created fingerprints achieved mixed results; however, manual adjustments of the parameters brought substantial improvements. Up to 72% of synthetic fingerprints reached the match by the VeriFinger. The results of the evaluation helped to identify weak points of the current solution. Based on these, the thesis proposes further steps to improve the success rate of automatic generation and the quality of other components.
|
|
|
Reconstruction and Enhancement of Damaged Parts of Fingerprint Images
Špila, Andrej ; Rydlo, Štěpán (referee) ; Heidari, Mona (advisor)
Táto práca sa zaoberá problémom rekonštrukcie snímkov odtlačkov prsta so zameraním na neobnovyteľné oblasti poškodené rôznymi kožnými ochoreniami. Generatívne súperi- ace siete s trénovateľnou konvolučnou vrstvou s gaborovými filtrami bola natrénovaná na dátovej sade reálnych snímkov odtlačkov prsta. Práca predvádza že natrénovaný model vie spoľahlivo rekonštruovať malé oblasti ľubovoľného tvaru a v prípade väčších oblastí, globálne skóre kvality rekonštruovaného odtlačku prsta získané využitím softvéru NIST biometric image software sa v porovnaní s originálnym snímkom navýšilo. Je navrhnutý štandardizovaný formát pre snímky odtlačkov prsta ktorý pomohol stabilizovat trénovanie generatívnych súperiacich sietí.
|
|
|
Synthetic Fingerprint Generation from Biometric Template
Šuba, Adam ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
The goal of this master thesis is to design and implement an approach for synthetic fingerprint generation from a biometric template. The thesis bases the solution on an existing fingerprint generator called SyFDaS developed at the Brno University of Technology, Faculty of Information Technology. Individual components of the generator had to be modified and automized to suit better the task of generating from a template. The end product enables the user to create a fingerprint without any intervention just by importing a template. The evaluation in this thesis presents results obtained by comparing the synthetic and original fingerprints using the VeriFinger algorithm. Entirely automatically created fingerprints achieved mixed results; however, manual adjustments of the parameters brought substantial improvements. Up to 72% of synthetic fingerprints reached the match by the VeriFinger. The results of the evaluation helped to identify weak points of the current solution. Based on these, the thesis proposes further steps to improve the success rate of automatic generation and the quality of other components.
|
|
|
Reconstruction of Damaged Parts of Fingerprint Image Using Neural Nets
Halinár, Michael ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
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.
|
guest ::
