Lane Markers Detection Based on Consecutive Threshold Segmentation

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Abstract:

This paper proposed a simple and robust lane markers detection method for intelligent vehicle navigation. It needs not calculate inverse perspective map. The method uses multiple threshold segmentation instead of single threshold segmentation. And straight and curve lane markers are directly extracted in Run-Length accumulation (RLA) images. It performs well in various complex conditions and costs less than 50 ms for a 352 by 288 image. Experiments on many kinds of real complex image sequences demonstrate the effectiveness and efficiency of the proposed method.

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Periodical:

Advanced Materials Research (Volumes 317-319)

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881-885

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Online since:

August 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] A. Borkar, M Hayes, M.T. Stmth, Detecting Lane markers in complex urban Environments. IEEE 7th international conference on mobile Adhoc and sensor systems. (2010).

DOI: 10.1109/mass.2010.5663812

Google Scholar

[2] Yong UK Yim, Se-Young Oh, Three-Feature based automatic lane detection algorithm for Autonomous Driving., IEEE Transaction on intelligent transportation system, vol.4, no.4,(2003) pp.219-224..

DOI: 10.1109/tits.2003.821339

Google Scholar

[3] C.G. Rotaru, T.J. Zhang, Extracting road feature from color image using a cognitive approach, IEEE intelligent vehicle symposium, (2004),pp.298-303.

DOI: 10.1109/ivs.2004.1336398

Google Scholar

[4] T.Y. Sun, S.J. Tsai, V.Chan, HIS color model based lane-marking detection, IEEE intelligent transportation systems conference , (2006), pp.1168-1172.

DOI: 10.1109/itsc.2006.1707380

Google Scholar

[5] Mohamed Aly, Real time detection of lane markers in urban streets. IEEE intelligent vehicles symposium, pp.7-12, June (2008).

DOI: 10.1109/ivs.2008.4621152

Google Scholar

[6] A. Borkar, M Hayes, M.T. Stmth S. Pankani, A Layered approach to robust lane detection at night. Computational intelligence in Vehicles and Vehicular systems, (2009).

DOI: 10.1109/civvs.2009.4938723

Google Scholar

[7] A. Borkar, M Hayes, M.T. Stmth, Robust lane detection and tracking with ransack and kalman filter. pp.3261-3264, International Conference on Image Processing,(2009).

DOI: 10.1109/icip.2009.5413980

Google Scholar

[8] Yue Wanga, Eam Khwang Teoha, Dinggang Shenb, Lane detection and tracking using B-Snake, Image and Vision Computing vol.22(2004), pp.269-280.

DOI: 10.1109/iciis.1999.810313

Google Scholar

[9] Kuo-Yu Chiu, Sheng-Fuu Lin, Lane detection using color-based segmentation. IEEE intelligent vehicles symposium, June,(2005),pp.706-711.

DOI: 10.1109/ivs.2005.1505186

Google Scholar