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- Title
Centroid Distance Shape Recognition for Real Time Low Complexity Traffic Sign Recognition.
- Authors
Emami, Hamidreza; Kandowan, Ramin Shaghaghi; Hosseini, Seyyed Abolfazl
- 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.
- Subjects
TRAFFIC signs &; signals; CENTROID; SUPPORT vector machines; RUNNING speed; SHAPE recognition (Computer vision); DRIVER assistance systems; DISTANCES
- Publication
Majlesi Journal of Telecommunication Devices, 2020, Vol 9, Issue 4, p159
- ISSN
2423-4117
- Publication type
Article
- DOI
10.29252/mjtd.9.4.159