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A New Traffic Sign Recognition Technique Taking Shuffled Frog-Leaping Algorithm into Account.
Demokri Dizji, Pouya; Joudaki, Saba; Kolivand, Hoshang.
Afiliação
  • Demokri Dizji P; Department of Computer Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran.
  • Joudaki S; Department of Computer Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran.
  • Kolivand H; School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, L3 3AF UK.
Wirel Pers Commun ; 125(4): 3425-3441, 2022.
Article em En | MEDLINE | ID: mdl-35789577
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article