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Demokri Dizji, P, Joudaki, S and Kolivand, H (2022) A New Traffic Sign Recognition Technique Taking Shuffled Frog-Leaping Algorithm into Account. Wireless Personal Communications. pp. 1-17. ISSN 0929-6212
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A New Traffic Sign Recognition Technique Taking Shuffled Frog-Leaping Algorithm into Account.pdf - Accepted Version Download (1MB) | Preview |
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.
| Item Type: | Article |
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| Additional Information: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11277-022-09718-7 |
| Uncontrolled Keywords: | HOG; Memeplex; SFLA; SVM; TSR; Unsupervised segmentation; Networking & Telecommunications; 0805 Distributed Computing; 0906 Electrical and Electronic Engineering; 1005 Communications Technologies |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Springer |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 05 Aug 2022 11:47 |
| Last Modified: | 28 Jun 2023 00:50 |
| DOI or ID number: | 10.1007/s11277-022-09718-7 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/17269 |
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