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A smart transport system is an important part of road sign recognition. The project was designed to improve driving and safety, accurately and effectively. It teaches traffic rules, road conditions, and lane guidance and help drivers to drive better and safer. It has two main stages: acquisition and recognition. The challenges involved in obtaining real time traffic signals and recognition and provided by this project. It tells us about how to deal with external images and the different approaches to color and shape and analysis. Although image processing plays an important role in attention to the road sign, especially in color analysis. Convolutional neural networks are widely used in the detection and recognition of road signs.
Keywords:
Convolutional neural network, detection and recognition, image processing, shape and color analysis.
Cite Article:
"Traffic Sign Recognition", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.361 - 364, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206062.pdf
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000205199
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator