TY - EJOUR
AU - Fartaj, Mehdi
AU - Ghofrani, Sedigheh
PY - 2024
DA - February
TI - Traffic Road Sign Detection and Classification
T2 - Majlesi Journal of Electrical Engineering
VL - 6
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/traffic-road-sign-detection-and-classification/
N2 - Traffic road sign detection is important to a robotic vehicle that automatically drives on roads. As the colors of most traffic road signs are blue and red, in this paper, we use Hue- Saturation- Intensity (HSI) color space for color based segmentation at first. Using important geometrical features, the road signs are detected perfectly. After segmentation, it turns to classify every detected road signs. For this purpose, we employ and compare the performance of three classifiers; they are distance to border (DTB), FFT sample of signature, and code matrix. In this work, we use the code matrix as an efficient classifier for the first time. Although the achieved accuracy by code matrix is greater than the two referred classifiers in average, the main advantage is simplicity and so less computational cost.
IS - 4
PB - OICC Press
KW - Cloud computing, DDoS attacks, Machine Learning, deep learning techniques, . ,, Road sign detection, road sign classification, code matrix 
EN -