Abstract

The image recognition system of traffic signs is one of the important elements needed by autonomous vehicles, which also these signs are a guide for autonomous vehicles. In this paper we propose a traffic signs image recognition by implementing Gabor wavelet feature extraction. The images of traffic signs will be captured by cameras. These images will then be processed for recognition. Where in the process the features of the traffic sign images will be extracted so that the identifier for each traffic sign is obtained. We use 8 orientations and 5 scales Gabor bank and PCA in recognition process to get a good accuracy as well as efficiency. Easiness and high accuracy was the avantages from proposed Gabor method. This method as seen from the experimental results demonstrate fair reasonable in terms of preciseness, with 90.55% overall average recognition rate are obtained for the data of 100 traffic sign images.

Original languageEnglish
Title of host publicationProceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages266-269
Number of pages4
ISBN (Electronic)9781538684481
DOIs
Publication statusPublished - Mar 2019
Event1st International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019 - Yogyakarta, Indonesia
Duration: 13 Mar 201915 Mar 2019

Publication series

NameProceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019

Conference

Conference1st International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019
Country/TerritoryIndonesia
CityYogyakarta
Period13/03/1915/03/19

Keywords

  • feature extraction
  • gabor wavelet component
  • traffic sign

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