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master's thesis
Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču
2021. urn:nbn:hr:200:164688
Opačak, Kristina
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Communications
Chair of Electronics and Microelectronics

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Opačak, K. (2021). Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču (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:200:164688

Opačak, Kristina. "Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:164688

Opačak, Kristina. "Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:164688

Opačak, K. (2021). 'Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču', Master's 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:200:164688

Opačak K. Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2021 [cited 2024 April 19] Available at: https://urn.nsk.hr/urn:nbn:hr:200:164688

K. Opačak, "Prostorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:200:164688

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Metadata
TitleProstorno filtriranje slike na realnoj razvojnoj platformi za napredne sustave za pomoć vozaču
Title (english)Image spatial filtering using real development platform for advanced driver assistance systems
AuthorKristina Opačak
MentorMarijan Herceg (mentor)
Committee memberMarijan Herceg (predsjednik povjerenstva)
Committee memberMario Vranješ (član povjerenstva)
Committee memberRatko Grbić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Communications)
(Chair of Electronics and Microelectronics)
Osijek
Defense date and country2021-09-16, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Telecommunications and Informatics
Abstract
U ovom radu implementirani su i uspoređeni različiti tipovi prostornih filtara. Najprije su predstavljeni osnovni tipovi šuma koji stvaraju potrebu za filtriranjem, a to su: Gaussov, šum „soli i papra“ te kvantni. Nakon toga su predloženi načini suzbijanja istih različitim tipovima filtara te je dan teorijski osvrt na četiri prostorna filtra: medijan, moving average, Gaussov i visokopropusni. Razvijeni algoritmi implementirani su na realnu razvojnu ADAS platformu s prilagođenim C kodom za Alpha ploču i kreiranim slučajevima upotrebe za svaki filtar za 3 različita rasporeda procesora: DSP, A15 i kombinacija dvaju DSP procesora. Dodatne kombinacije filtara i procesora su filtri s različitim veličinama kernela i različitim rezolucijama. Svaka od navedenih kombinacija se testirala na testnom skupu od deset slika. Rezultati su uspoređeni te je utvrđeno da se najbrže izvodi visokopropusni filtar, a najsporije medijan. Ovisno o primjeni, može se koristiti veća rezolucija, ali ona, kao i povećanje veličine kernela, uzrokuje smanjenje brzine izvođenja.
Abstract (english)
In this paper were implemented and compared different types of spatial filters. Firstly, the basic types of noise, which create the need for spatial filters, are described. Common types of noise are: Gaussian, „salt and pepper“ and quantization noise. After that are named and described different types of spatial filters used for reducing noises in digital image. These filters are: median, moving average, Gaussian and highpass filter. The developed algorithms are implemented on a real ADAS development platform with custom C code for Alpha board and created usecases for each filter for three different CPU-s: DSP, A15 and a combination of two DSP CPU-s in parallel. Aditional combinations are three different resolution and three different kernel sizes in each filter. Each of this combinations were tested on a test set of ten images. The results were compared and it was found that high pass filter is the fastest, and median the slowest. Depending on the application, a higher resolution can be used, but it, as well as increasing the kernel size, causes a decrease in execution speed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:164688
Study programmeTitle: UNIVERSITY STUDY AUTOMOBILE COMPUTER AND COMMUNICATION
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka automobilskog računarstva i komunikacija (magistar/magistra inženjer/inženjerka automobilskog računarstva i komunikacija)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-10-05 14:20:47