prikaz prve stranice dokumenta Integracija openCV biblioteke u React Native android aplikaciju
  Download
PDF 1.33 MB
undergraduate thesis
Integracija openCV biblioteke u React Native android aplikaciju
2024. urn:nbn:hr:200:433286
Malnar, Luka
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

Cite this document

Malnar, L. (2024). Integracija openCV biblioteke u React Native android aplikaciju (Undergraduate 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:200:433286

Malnar, Luka. "Integracija openCV biblioteke u React Native android aplikaciju." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:433286

Malnar, Luka. "Integracija openCV biblioteke u React Native android aplikaciju." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:433286

Malnar, L. (2024). 'Integracija openCV biblioteke u React Native android aplikaciju', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 10 December 2024, https://urn.nsk.hr/urn:nbn:hr:200:433286

Malnar L. Integracija openCV biblioteke u React Native android aplikaciju [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2024 [cited 2024 December 10] Available at: https://urn.nsk.hr/urn:nbn:hr:200:433286

L. Malnar, "Integracija openCV biblioteke u React Native android aplikaciju", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:200:433286

Please login to the repository to save this object to your list.
Metadata
TitleIntegracija openCV biblioteke u React Native android aplikaciju
Title (english)Integration of openCV library into React Native android application
AuthorLuka Malnar
MentorHrvoje Leventić (mentor)
Committee memberHrvoje Leventić (predsjednik povjerenstva)
Committee memberKrešimir Romić (član povjerenstva)
Committee memberMarin Benčević (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2024-09-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Program Engineering
Abstract
U ovom radu istražena je i implementirana integracija OpenCV biblioteke u React Native Android aplikaciju s ciljem automatizacije rješavanja sudoku zagonetki. Prikazan je cijeli postupak, počevši od preuzimanja i postavljanja OpenCV-a, preko obrade slike za prepoznavanje sudoku polja, do korištenja konvolucijske neuronske mreže (CNN) za prepoznavanje znamenki unutar polja. Razvijeni CNN model treniran je u Pythonu i integriran u aplikaciju putem TensorFlow.js, omogućujući brzu i točnu klasifikaciju znamenki. Aplikacija omogućava korisnicima da jednostavno slikaju sudoku zagonetku, prepoznaju znamenke i dobiju rješenje u stvarnom vremenu. Rezultati pokazuju visoku preciznost i efikasnost rješenja, što aplikaciju čini korisnički prijateljskom.
Abstract (english)
This work explores and implements the integration of the OpenCV library into a React Native Android application with the aim of automating the solving of Sudoku puzzles. The entire process is detailed, beginning with downloading and setting up OpenCV, followed by image processing to recognize Sudoku grids, and utilizing a Convolutional Neural Network (CNN) for recognizing digits within the grid. The developed CNN model was trained in Python and integrated into the application via TensorFlow.js, enabling fast and accurate digit classification. The application allows users to easily capture a Sudoku puzzle with their camera, recognize the digits, and obtain a solution in real-time. The results demonstrate high accuracy and efficiency, making the application user-friendly.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:433286
Study programmeTitle: Graduate university study programme in Computer Engineering
Study programme type: professional
Study level: undergraduate
Academic / professional title: prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-10-14 09:23:17