Highway Lane Detection Based on a New Gray Method

Article Preview

Abstract:

a new gray method is provided in this paper for highway lane detection. Firstly, the novel gray method transform an RGB color image to a gray-level image based on a new gray vector. To deal with illumination changes, the new gray vector is updated on real-time.Secondly,the canny edge detector’s threshold values are decided adaptive.Lastly,Hough transform method realizes the detection of lanes. For different time in a day, experiments indicate that the proposed algorithm has good results.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 1044-1045)

Pages:

1553-1557

Citation:

Online since:

October 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Y. Chen,M. He,Y.F. Zhang, Robust Lane Detection Based on Gradient Direction,J. IEEE Conference on Industrial Electronics and Applications. (2011)1547-1552.

DOI: 10.1109/iciea.2011.5975836

Google Scholar

[2] H. Yoo,U. Yang,K. Sohn, Gradient-Enhancing Conversion for Illumination-Robust Lane Detection,J. IEEE Transactions on intelligent transportation systems. 14(3)(2013)1083-1094.

DOI: 10.1109/tits.2013.2252427

Google Scholar

[3] Z. Kim, Robust lane detection and tracking in challenging scenarios ,J. IEEE Trans. Intell. transp. syst. (2008)16-26.

DOI: 10.1109/tits.2007.908582

Google Scholar

[4] J. Wang,Y. Wu and Z. Liang, Lane detection and tracking using a layered approach,J. Proc. IEEE Int. Conf. Inf. Atom, Harbin, China. (2010)1735-1740.

Google Scholar

[5] X.F. Fang, W. Bo,Z.Z. Qiang, Real-Time Lane Detection for Intelligent Vehicles Based on Monocular Vision,J. proceeding of the 31st Chinese Control Conference. (2012)7332-7337.

Google Scholar

[6] N. Mechat, N. Saadia N.K. M'Sirdi, Lane Detection and Tracking by Monocular Vision System in Road Vehicle,J. 5th International Congress on Image and Signal Processing. (2012)1276-1282.

DOI: 10.1109/cisp.2012.6469683

Google Scholar

[7] X. Liu,B. Dai,B. Zhang, Real-time Long-range Lane Detection and Tracking for Intelligent Vehicle, j. International Conference on Image and Graphics. (2011)654-659.

DOI: 10.1109/icig.2011.116

Google Scholar

[8] K.H. Lim, K.P. Seng, L. Minn, Lane Detection and Kalman-based Linear-Parabolic Lane Tracking,J. International Conference on Intelligent Human-Machine Systems and Cybernetics. (2009)351-354.

DOI: 10.1109/ihmsc.2009.211

Google Scholar

[9] G.L. Liu,F. Wörgötter,I. Markelic', Stochastic Lane Shape Estimation Using Local Image Descriptors,J. IEEE Transactions on intelligent transportation systems. 14(1)(2013)13-21.

DOI: 10.1109/tits.2012.2205146

Google Scholar

[10] G.L. Liu,F. Wörgötter,I. Markelic', Combining statistical Hough transform and particle filter for robust lane detection and tracking. Intelligent Vehicles Symp, San Diego, CA(2010)993–997.

DOI: 10.1109/ivs.2010.5548021

Google Scholar