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master's thesis
Kontrola pristupa vozila pomoću računalnog vida
2017. urn:nbn:hr:200:282184
Rukavina, Dominik-Martin
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

Cite this document

Rukavina, D. M. (2017). Kontrola pristupa vozila pomoću računalnog vida (Master's thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:282184

Rukavina, Dominik Martin. "Kontrola pristupa vozila pomoću računalnog vida." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2017. https://urn.nsk.hr/urn:nbn:hr:200:282184

Rukavina, Dominik Martin. "Kontrola pristupa vozila pomoću računalnog vida." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2017. https://urn.nsk.hr/urn:nbn:hr:200:282184

Rukavina, D. M. (2017). 'Kontrola pristupa vozila pomoću računalnog vida', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 09 May 2021, https://urn.nsk.hr/urn:nbn:hr:200:282184

Rukavina DM. Kontrola pristupa vozila pomoću računalnog vida [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2017 [cited 2021 May 09] Available at: https://urn.nsk.hr/urn:nbn:hr:200:282184

D. M. Rukavina, "Kontrola pristupa vozila pomoću računalnog vida", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:200:282184

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Metadata
TitleKontrola pristupa vozila pomoću računalnog vida
Title (english)Vehicle access control using computer vision
AuthorDominik-Martin Rukavina
MentorRatko Grbić (mentor)
Committee memberRatko Grbić (predsjednik povjerenstva)
Committee memberEmmanuel Karlo Nyarko (član povjerenstva)
Committee memberIvan Vidović (član povjerenstva)
GranterJosip 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 country2017-12-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Process Computing
Abstract
Rad se bavi izradom ANPR sustava za automatsku identifikaciju vozila na temelju jedinstvene registracijske oznake. U radu je dano rješenje zasnovano na računalnom vidu. Sustav se sastoji od Raspberry Pi 3B mikroračunala, Raspberry Pi NOIR kamere, te programske podrške napisane u C++ programskom jeziku i implementirane u QT okruženju pomoću OpenCV biblioteke. Implementirano programsko rješenje je predstavljeno kao niz algoritama koji se slijedno izvode. Algoritmi za prepoznavanje registracijske oznake su: algoritam za predobradu ulazne fotografije, algoritam za pronalaženje i lokalizaciju registracijske pločice, algoritam za pronalazak znakova na registracijskoj pločici, algoritam za izdvajanje i optičko prepoznavanje znakova. U radu se koristi Tesseract biblioteka kao sustav za optičko prepoznavanje znakova. Na posljetku se izvodi provjera prava pristupa korisnika. Predstavljeno je potpuno rješenje s SQLite bazom podataka. Prikazani sustav ima točnost od 99%.
Abstract (english)
This paper deals with implementing ANPR system for automatic vehicle identification based on number plates. This paper shows approach based on computer vision. The system consists of a Raspberry Pi microcomputer, Raspberry Pi NOIR camera and accompanying software. The software is written using C++ programming language and implemented in QT environment with the OpenCV computer vision library. The application is presented as a series of algorithms which are performed in sequential matter. Algorithms include: algorithm for data preprocesing, algorithm for number plate identification and localization, character segmentation and optical character recognition. Tesseract library is used for optical character recognition. Last step is access control. Application uses integrated SQLite database. Application has accuracy of approximately 99%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:282184
Study programmeTitle: 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 resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2018-01-29 16:30:28