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Pregled bibliografske jedinice broj: 1170865

Implementation of different image edge detection algorithms on a real embedded ADAS platform


Ćorić, Dario; Kaštelan, Ivan; Herceg, Marijan; Pjevalica, Nebojša
Implementation of different image edge detection algorithms on a real embedded ADAS platform // 2021 Zooming Innovation in Consumer Technologies Conference (ZINC) / Bjelica, Milan (ur.).
Novi Sad: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 193-197 doi:10.1109/ZINC52049.2021.9499254 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Implementation of different image edge detection algorithms on a real embedded ADAS platform

Autori
Ćorić, Dario ; Kaštelan, Ivan ; Herceg, Marijan ; Pjevalica, Nebojša

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2021 Zooming Innovation in Consumer Technologies Conference (ZINC) / Bjelica, Milan - Novi Sad : Institute of Electrical and Electronics Engineers (IEEE), 2021, 193-197

ISBN
978-1-6654-0417-4

Skup
Zooming Innovation in Consumer Technologies Conference (ZINC 2021)

Mjesto i datum
Novi Sad, Srbija, 26.05.2021. - 27.05.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
edge detection ; ADAS platform ; VisionSDK

Sažetak
Advanced Driver-Assistance Systems (ADASs) are becoming more and more popular in modern vehicles in the last years. A number of them are based on processing the images captured by in-vehicle cameras. Furthermore, in image processing-based ADAS algorithms one of the most important steps often is edge detection. Therefore, it is important to properly choose the edge detection method, to achieve high performance and low processing time. Due to limited hardware resources available when using real ADAS platforms, the trade-off is needed. In this paper, the implementation of four different edge detection operators (Sobel, Prewitt, Laplace and Canny) onto a real ADAS Alpha board is performed. The implementation is performed using the Vision Software Development Kit (SDK), which is a multi- processor software platform specifically optimized to work with Texas Instruments (TI) Systems-On- Chip (SoCs) that Alpha board consists of. To test the operators’ performance in a real ADAS operational environment, the Berkeley dataset is used. The output results of each edge detector are compared to available ground truth labeled images from the Berkeley dataset to check which detector achieves the highest performance in terms of edge detection accuracy. Furthermore, the operators are compared in terms of execution time and memory usage. It was shown that Canny operator requires the longest execution time and the highest amount of memory, but it also achieves the highest edge detection accuracy. It is also shown that the trade-off between detector accuracy and its requirements can be achieved in certain situations where it is acceptable.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Marijan Herceg (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Ćorić, Dario; Kaštelan, Ivan; Herceg, Marijan; Pjevalica, Nebojša
Implementation of different image edge detection algorithms on a real embedded ADAS platform // 2021 Zooming Innovation in Consumer Technologies Conference (ZINC) / Bjelica, Milan (ur.).
Novi Sad: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 193-197 doi:10.1109/ZINC52049.2021.9499254 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Ćorić, D., Kaštelan, I., Herceg, M. & Pjevalica, N. (2021) Implementation of different image edge detection algorithms on a real embedded ADAS platform. U: Bjelica, M. (ur.)2021 Zooming Innovation in Consumer Technologies Conference (ZINC) doi:10.1109/ZINC52049.2021.9499254.
@article{article, author = {\'{C}ori\'{c}, Dario and Ka\v{s}telan, Ivan and Herceg, Marijan and Pjevalica, Neboj\v{s}a}, editor = {Bjelica, M.}, year = {2021}, pages = {193-197}, DOI = {10.1109/ZINC52049.2021.9499254}, keywords = {edge detection, ADAS platform, VisionSDK}, doi = {10.1109/ZINC52049.2021.9499254}, isbn = {978-1-6654-0417-4}, title = {Implementation of different image edge detection algorithms on a real embedded ADAS platform}, keyword = {edge detection, ADAS platform, VisionSDK}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Novi Sad, Srbija} }
@article{article, author = {\'{C}ori\'{c}, Dario and Ka\v{s}telan, Ivan and Herceg, Marijan and Pjevalica, Neboj\v{s}a}, editor = {Bjelica, M.}, year = {2021}, pages = {193-197}, DOI = {10.1109/ZINC52049.2021.9499254}, keywords = {edge detection, ADAS platform, VisionSDK}, doi = {10.1109/ZINC52049.2021.9499254}, isbn = {978-1-6654-0417-4}, title = {Implementation of different image edge detection algorithms on a real embedded ADAS platform}, keyword = {edge detection, ADAS platform, VisionSDK}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Novi Sad, Srbija} }

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