Centroid Distance Shape Recognition for Real Time Low Complexity Traffic Sign Recognition

Majlesi Journal of Telecommunication Devices

مقاله 4، دوره 9، شماره 4، اسفند 2020، صفحه 159-162   

نوع مقاله: Articles

نویسندگان

Hamidreza Emami^* ؛ Ramin Shaghaghi Kandowan؛ Seyyed Abolfazl Hosseini

Yadegar-e-Imam Khomeini(RAH)Shahre Rey Branch, Islamic Azad University, Tehran, Iran.

چکیده

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.

کلیدواژه‌ها

Traffic Sign Recognition؛ Advanced Driver Assistance Systems؛ Centroid Distance؛ Histogram of Oriented Gradients؛ HOG؛ Support vector machine؛ SVM؛ Shape Recognition؛ Low-Complexity

مراجع

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