Traffic Sign Detection and Recognition

Authors

  • Dr.Hazeem Baqer Tahar Computer Sciences Department , College of Education for pure Sciences, University of Thi-Qar.
  • Sahar Rayad Abdul kadeem Computer Sciences Department , College of Education for pure Sciences, University of Thi-Qar.

DOI:

https://doi.org/10.32792/jeps.v10i1.42

Keywords:

Traffic sign, detection and recognition, gray level, RGB, a Similarity metrics, correlation Coefficient

Abstract

Through dealing with technologies and technology, in field use image processing in the systems of
electronic Including smart driving systems for cars. In order to facilitate and improve the performance of
electronic systems. Some mathematical concepts and algorithms are employed for this purpose. Where
traffic Sign Detection and Recognition (TSDR) systems provide an additional level to driver assistance,
leading to improve safety for passengers, road users and vehicles. As part of Advanced Driving Assistance
Systems (ADAS), ADAS helps the driver to drive the car and leads to a better awareness on the road.
proposed system for the detection of traffic signs, classification into danger, information, obligation and
prohibition classes.
Through this research we aim to provide a system capable of taking images of traffic signals on both sides
of the road, Analyze and recognition its and alert the driver to what the sign image mean. The driver will
be able to act on the instructions in the traffic sign. The traffic system helps drivers recognize signs they
did not recognize before. The operation is performed using a Similarity metrics were using correlation for
Complete the matching process between the resulting image and the stored image in the database

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Published

2020-12-03

Issue

Vol. 10 No. 1 (2020)

Section

Articles

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