Citation

Demokri Dizji P, Joudaki S, Kolivand H. Wirel. Personal Commun. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s11277-022-09718-7

PMID

35789577

PMCID

PMC9244287

Abstract

Everyday humans use cars to move faster, and the world is a chaotic place, and a little distraction or a mistake could be the reason for an accident and bring people great pain. An assistance system that can distinguish and detect signs on the roads and brings the driver's attention to road signs and make them aware of their meaning could be beneficial. The most important part of the Traffic Sign Recognition System is the algorithm. In this paper, a new way toward Traffic Sign Recognition algorithm taking the advantages of Color Segmentation, support vector machines, and histograms of oriented gradients on the GTSRB dataset is proposed. The unsupervised shuffled frog-leaping algorithm is employed for segmenting the images. The results show remarkable improvements by using meta-heuristic algorithms.

Language: en

Keywords

SVM; HOG; Memeplex; SFLA; TSR; Unsupervised segmentation