Pregled bibliografske jedinice broj: 1128122
Recognition of maximal speed limit traffic signs for use in advanced ADAS algorithms
Recognition of maximal speed limit traffic signs for use in advanced ADAS algorithms // 2021 Zooming Innovation in Consumer Technologies Conference (ZINC)
Novi Sad, 2021. str. 21-26 doi:10.1109/ZINC52049.2021.9499300 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1128122 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Recognition of maximal speed limit traffic signs
for use in advanced ADAS algorithms
Autori
Strišković, Barbara ; Vranješ, Mario ; Vranješ, Denis ; Popović, Miroslav
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2021 Zooming Innovation in Consumer Technologies Conference (ZINC)
/ - Novi Sad, 2021, 21-26
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
ADAS ; convolutional neural network ; deep learning ; traffic sign classification
Sažetak
Advanced Driver Assistance Systems (ADAS) have been increasingly developing, specifically in the last decade. One of such ADAS is that intended for traffic signs recognition. This paper deals with the recognition of a specific subset of traffic signs, i.e. speed limit traffic signs. The complete solution is based on the usage of machine learning and finally implemented in the C programming language. After the optimization process, the final solution is implemented on the real ADAS board, to check its performance in a real operational environment. Due to the limited resources of the ADAS board itself, a simple Convolutional Neural Network (CNN) was created to recognize speed limit traffic signs. For CNN training a large database of 6891 training images is used. When testing the solution, 731 test images from the real traffic are used, as well as 123 real video sequences. The test results show that in certain situations the proposed solution is capable of achieving high performance in terms of precision, while in some cases additional improvements of the solution should be investigated. It is capable of processing 12 frames per second when operating with state-of- the-art automotive camera resolution, i.e. 1280x720 pixels.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
DGS-UNIOS-ZUP 2018-6 - Povećavanje razine pouzdanosti vožnje autonomnih vozila pomoću sustava kamera na vozilu (Vranješ, Mario, DGS - Interni natječaja Sveučilišta Josipa Jurja Strossmayera u Osijeku za znanstvenoistraživačke i umjetničke projekte UNIOS-ZUP 2018) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek