Title of article :
Centroid Distance Shape Recognition for Real Time Low Complexity Traffic Sign Recognition
Author/Authors :
Emami ، Hamidreza Islamic Azad University,Yadegar-e-Imam Khomeini(RAH)Shahre Rey Branch , Shaghaghi Kandowan ، Ramin Islamic Azad University,Yadegar-e-Imam Khomeini(RAH)Shahre Rey Branch , Hosseini ، Abolfazl Islamic Azad University,Yadegar-e-Imam Khomeini(RAH)Shahre Rey Branch
Abstract :
This paper represents advantages of using Centroid distance function for shape detection in real time traffic sign recognition compared with extracting histogram of oriented gradients (HOG) features and using support vector machine (SVM) classifier. Simulation results of using centroid distance show similar accuracy in compare with HOG SVM while have very low complexity and cost and running with higher speed.
Keywords :
Traffic Sign Recognition , Advanced Driver Assistance Systems , Centroid Distance , Histogram of Oriented Gradients , HOG , Support Vector Machine , SVM , Shape Recognition , Low , Complexity
Journal title :
Majlesi Journal of Telecommunication Devices
Journal title :
Majlesi Journal of Telecommunication Devices
