Traffic Signs Detection and Tracking using Modified Hough Transform

Pavel Yakimov, Vladimir Fursov

2015

Abstract

Traffic Signs Recognition (TSR) systems can not only improve safety, compensating for possible human carelessness, but also reduce tiredness, helping drivers keep an eye on the surrounding traffic conditions. This paper proposes an efficient algorithm for real-time TSR. The article considers the practicability of using HSV color space to extract the red color. An algorithm to remove noise to improve the accuracy and speed of detection was developed. A modified Generalized Hough transform is then used to detect traffic signs. The current velocity of a vehicle is then used to predict the sign’s location in the adjacent frames in a video sequence. Finally, the detected objects are being classified. The developed algorithms have been tested using real scene images and the German Traffic Sign Detection Benchmark (GTSDB) dataset and showed efficient results.

References

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Paper Citation


in Harvard Style

Yakimov P. and Fursov V. (2015). Traffic Signs Detection and Tracking using Modified Hough Transform . In Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2015) ISBN 978-989-758-118-2, pages 22-28. DOI: 10.5220/0005543200220028


in Bibtex Style

@conference{sigmap15,
author={Pavel Yakimov and Vladimir Fursov},
title={Traffic Signs Detection and Tracking using Modified Hough Transform},
booktitle={Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2015)},
year={2015},
pages={22-28},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005543200220028},
isbn={978-989-758-118-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2015)
TI - Traffic Signs Detection and Tracking using Modified Hough Transform
SN - 978-989-758-118-2
AU - Yakimov P.
AU - Fursov V.
PY - 2015
SP - 22
EP - 28
DO - 10.5220/0005543200220028