Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka

Matoš, Ivona

undergraduate thesis

Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka

Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. urn:nbn:hr:200:928216

Matoš, Ivona

Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Programming Languages and Systems

Cite this document

APA 6th Edition

Matoš, I. (2018). Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka (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:200:928216

MLA 8th Edition

Matoš, Ivona. "Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. https://urn.nsk.hr/urn:nbn:hr:200:928216

Chicago 17th Edition

Harvard

Matoš, I. (2018). 'Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 19 April 2024, https://urn.nsk.hr/urn:nbn:hr:200:928216

Vancouver

Matoš I. Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2018 [cited 2024 April 19] Available at: https://urn.nsk.hr/urn:nbn:hr:200:928216

IEEE

I. Matoš, "Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:200:928216

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:928216

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Metadata

Title	Prepoznavanje znakova ograničenja brzine iz postojećih baza podataka
Title (english)	The speed limit road signs recognition using existing road sign image databases
Author	Ivona Matoš
Mentor	Zdravko Krpić (mentor)
Mentor	Krešimir Romić (mentor)
Committee member	Zdravko Krpić (predsjednik povjerenstva)
Committee member	Tomislav Matić (član povjerenstva)
Committee member	Alfonzo Baumgartner (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek (Department of Software Engineering) (Chair of Programming Languages and Systems) Osijek
Defense date and country	2018-09-12, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Data Processing
Abstract	Metoda potpornih vektora jedna je od najučinkovitijih za rješavanje problema prepoznavanja prometnih znakova. U ovom radu predstavljena je aplikacija za prepoznavanje znakova ograničenja brzine iz baze slike znakova. Aplikacija koristi standardni medijan i Gaussov filtar za uklanjanje šuma iz slika, Houghovu transformaciju za detekciju kružnog objekta i metodu potpornih vektora za prepoznavanje znaka. Prilikom implementacije metode potpornih vektora, bilo je potrebno klasificirati i istrenirati set slika iz baze rMASTIF. Analizom algoritma, uspostavljeni su prikladni parametri svih upotrijebljenih funkcija za postizanje optimalnih rezultata u većini slučajeva. Isto tako, prilikom detekcije pronađeni su primjeri gdje je nužno promijeniti parametre za postizanje točnih rezultata. Također, utvrđeni su primjeri iznimno loše kvalitete slike nad kojima je nemoguće obaviti detekciju. Usprkos tome, trening nad bazom uspješno je proveden te je testiranjem implementirane metode utvrđeno kako u većini slučajeva algoritam pravilno predviđa zadani prometni znak.
Abstract (english)	A support vector machine is one of the most efficient methods used for traffic sign recognition. In this paper application for speed limit traffic sign recognition from a traffic sign image database is presented. The application uses standard median filter and Gaussian filter for removing noise in corrupted images, Hough transformation for detection of a circular object within an image and a support vector machine for sign recognition. During the implementation of the support vector machine, it is necessary to classify and train a set of images taken from the rMASTIF database. While analyzing the algorithm adequate parameters are established for every function used, in order to achieve as optimal results as possible. Also, a few examples are found where changing the parameters is necessary to obtain accurate results. In addition, there are a few images in which it is impossible to detect a circle due to images’ bad quality. Despite identifying significant amount of problems, the support vector machine is successfully trained and tested. In most cases, the algorithm accurately predicting a speed sign in the tested images is established.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:200:928216
Study programme	Title: Undergraduate University Study Programme in Computer Engineering Study programme type: university Study level: undergraduate Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Repository	Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Created on	2018-09-26 13:15:55