Title of article :
Traffic Road Sign Detection and Classification
Author/Authors :
Fartaj، Mehdi نويسنده Department of Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran. , , Ghofrani، Sedigheh نويسنده Electrical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran ,
Issue Information :
فصلنامه با شماره پیاپی 23 سال 2012
Abstract :
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.
Journal title :
Majlesi Journal of Electrical Engineering
Journal title :
Majlesi Journal of Electrical Engineering