A Review on Real-time Traffic Light Detection Methods

Authors

  • Purohit Harshangi N.  Students, Electronics &Communication, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Parmar Shivangi J.  Students, Electronics &Communication, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Patel Shreya H.  Students, Electronics &Communication, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Borse Bhavika M.  Students, Electronics &Communication, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Patel Viral J.  Assistant Professor, Electronics & Communication, Sigma institute of Engineering, Vadodara, Gujarat, India

Keywords:

Color Based, Edge Based, Density Based, Background Subtraction, Hough Transform.

Abstract

This research paper is conducted to detect crosswalks and traffic lights with small false positive and negative errors. The current reliable traffic light recognition algorithms operate well under way, most of them are mainly designed for detection at a fixed position and effect on autonomous vehicles under real-world conditions is still limited. The paper is presented a camera-based algorithm for the problem. The image processing flow can be divided into three steps, including pre-processing, detection and recognition. In this paper, they proposed a novel vision-based traffic light detection method for driving vehicles, which is fast and robust under different illumination conditions.

References

  1. Saini, S., Nikhil, S., Konda, K. R., Bharadwaj, H. S., & Ganeshan, N. (2017). An efficient vision-based traffic light detection and state recognition for autonomous vehicles. 2017 IEEE Intelligent Vehicles Symposium (IV). doi:10.1109/ivs.2017.7995785
  2. Shi, Z., Zou, Z., & Zhang, C. (2016). Real-Time Traffic Light Detection With Adaptive Background Suppression Filter. IEEE Transactions on Intelligent Transportation Systems, 17(3), 690-700. doi:10.1109/tits.2015.2481459
  3. Tran, T. H., Pham, C. C., Nguyen, T. P., Duong, T. T., & Jeon, J. W. (2016). Real-time traffic light detection using color density. 2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). doi:10.1109/icce-asia.2016.7804791
  4. Sathiya, S., Balasubramanian, M., & Priya, D. V. (2014). Real time recognition of traffic light and their signal count-down timings. International Conference on Information Communication and Embedded Systems (ICICES2014). doi:10.1109/icices.2014.7033965
  5. Choi J., Ahn, B. T., & Kweon, I. S. (2013). Crosswalk and traffic light detection via integral framework. The 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision. doi:10.1109/fcv.2013.6485511
  6. Yu, C., Huang, C., & Lang, Y. (2010). Traffic light detection during day and night conditions by a camera. IEEE 10th International Conference On Signal Processing proceedings. Doi:10.1109/Icosp.2010.5655934
  7. Charette, R. D., & Nashashibi, F. (2009). Real time visual traffic lights recognition based on Spot Light Detection and adaptive traffic lights templates. 2009 IEEE Intelligent Vehicles Symposium. doi:10.1109/ivs.2009.5164304
  8. Omachi, M., & Omachi, S. (2009). Traffic light detection with color and edge information. 2009 2nd IEEE International Conference on Computer Science and Information Technology. doi:10.1109/iccsit.2009.5234518

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-04-10

Issue

Volume 4, Issue 5, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Purohit Harshangi N., Parmar Shivangi J., Patel Shreya H., Borse Bhavika M., Patel Viral J., " A Review on Real-time Traffic Light Detection Methods, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 5, pp.466-470, March-April-2018.