Beskontaktni sustav za prepoznavanje otisaka prstiju

Gojić, Andreja

master's thesis

Beskontaktni sustav za prepoznavanje otisaka prstiju

Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. urn:nbn:hr:200:390866

Gojić, Andreja

Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Institutional repository: Faculty of Electrical Engineering, Computer Science and Information Technology Osijek

Cite this document

APA 6th Edition

Gojić, A. (2023). Beskontaktni sustav za prepoznavanje otisaka prstiju (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:390866

MLA 8th Edition

Gojić, Andreja. "Beskontaktni sustav za prepoznavanje otisaka prstiju." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:390866

Chicago 17th Edition

Harvard

Gojić, A. (2023). 'Beskontaktni sustav za prepoznavanje otisaka prstiju', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 30 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:390866

Vancouver

Gojić A. Beskontaktni sustav za prepoznavanje otisaka prstiju [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2024 May 30] Available at: https://urn.nsk.hr/urn:nbn:hr:200:390866

IEEE

A. Gojić, "Beskontaktni sustav za prepoznavanje otisaka prstiju", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:390866

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:390866

Metadata

Title	Beskontaktni sustav za prepoznavanje otisaka prstiju
Title (english)	Contactless fingerprint recognition system
Author	Andreja Gojić
Mentor	Ratko Grbić (mentor)
Committee member	Ratko Grbić (predsjednik povjerenstva)
Committee member	Marijan Herceg (član povjerenstva)
Committee member	Mario Vranješ (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek (Department of Computer Engineering and Automation) (Chair of Automation and Robotics) Osijek
Defense date and country	2023-09-26, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Artificial Intelligence
Abstract	U ovom diplomskom radu izrađen je beskontaktni sustav za prepoznavanje otisaka prstiju. Prije svega dan je pregled dosadašnjih rješenja koji se temelje na tri metode, metoda za izdvajanje detalja, dubokim učenjem te kombinacije tih dviju metoda. Zatim je opisano predloženo rješenje u ovom radu. Budući da nije pronađen odgovarajući skup podataka za učenje neuronske mreže, izrađen je vlastiti skup podataka koji je služio za treniranje i testiranje neuronske mreže. Sustav se temelji na sijamskoj neuronskoj mreži koja se sastoji od dvije neuronske mreže. Sijamska neuronska mreža na ulazu prima dvije RGB slike na kojima su prikazani otisci prstiju, slike se predaju neuronskoj mreži čiji su izlazi vektori značajki. Zatim se računa euklidska udaljenost između dobivenih vektora koja predstavlja mjeru sličnosti u intervalu između 0 i 1. Izlaz iz mreže će biti bliže 1 ukoliko su otisci prstiju različiti ili bliže 0 ukoliko su otisci prstiju sličniji. Istrenirani model je implementiran na NVIDIA Jetson Nano te je izrađeno fizičko okruženje s ugrađenom kamerom i LED trakom koja služi za slikanje otisaka prstiju. Izrađena sijamska neuronska mreža evaluirana je na skupu podataka za testiranje i iz rezultata testiranja je vidljivo kako ima mjesta za napredak.
Abstract (english)	In this master thesis, a non-contact system for recognizing fingerprints was developed. Firstly, an overview of the previous solutions based on three methods, methods for extracting details, deep learning and a combination of these two methods is given. Then the solution proposed in this paper is described. Since no suitable data set was found for learning the neural network, an own data set was created that was used for training and testing the neural network. The system is based on a Siamese neural network consisting of two neural networks. Siamese neural network at the input receives two RGB images on which fingerprints are displayed, the images are given to the neural network whose outputs are feature vectors. Then the Euclidean distance between the obtained vectors is calculated, which represents a measure of similarity in the interval between 0 and 1. The output from the network will be closer to 1 if the fingerprints are different or closer to 0 if the fingerprints are more similar. The trained model was implemented on NVIDIA Jetson Nano and a physical environment was created with a built-in camera and an LED strip used for fingerprint imaging. The constructed Siamese neural network was evaluated on the test data set and the test results show that there is room for improvement.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:200:390866
Study programme	Title: Graduate University Study Programme in Computer Engineering Study programme type: university Study level: graduate Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Created on	2023-10-09 09:49:23

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