Fast lane recognition based on morphological multi-structure element model

Abstract

This paper proposes a lane detection algorithm based on multi-structure element model of morphological. The innovative point of the algorithm lies in the facts that the flexible structure has the multi-structure elements that lane model features have, and that the algorithm adopts the morphological filtering principle to extract the pixels in the image, which is similar to the lane model. In the algorithm, the interested area is extracted by a model of trapezium from original image, which is detected by the operator of Canny, and the lanes are extracted by the structure elements, which have similar characteristics to that of lane model. Several lines are detected by Hough transformation, then the traffic lanes are reconstructed. Experiments show that this algorithm is simple and robust, and can efficiently detect the lane mask accurately and quickly.

Keywords

Interested Area / Intelligent Transportation System / Hough Transformation / Intelligent Vehicle / Lane Detection

References

[1] YajunF., IchiroM., BertholdH.. IEEE transactions on intelligent transportation systems, 2002, 3: 196

[2] DuchowC., FriedlM.. TM-Echnisches Messen, 2008, 75: 464

[3] QingL., NanningZ., HongC.. IEEE Transactions on Intelligent Transportation Systems (1524–9050), 2004, 5: 300

[4] ZuWhanK.. IEEE Transactions on Intelligent Transportation Systems, 2008, 9: 16

[5] ChenY., WuD.-h.. Journal of System Simulation, 2008, 19: 5063

[6] KimZ.. Proc IEEE Workshop on Application of Computer Vision, 2005, 20: 455

[7] GregorR., LutzelerM.. IEEE Trans On ITS(1524-9050), 2002, 3: 49

[8] PangyuJ., SergiuN.. IEEE Transaction on Circuits and Systems for Video Technology, (1051–8215), 2005, 15: 528

[9] Hsu-YungC., Bor-ShemJ., et al.. IEEE Transactions on Intelli gent Transportation Systems, (1524–9050), 2006, 7: 571

[10] Assidiq A. A. M., Khalifa O.O. and Islam R., et al. Computer and Communication Engineering, Kuala Lumpur Malaysia, (2008), 82.

[11] Lipski C, Scholz B and Berger K, et al, IEEE Southwest Symposium on Image Analysis and Interpretation, Santa Fe NM, USA, MAR 24-26 (2008), 57.

[12] RomualdA., RolandC., FredericC.. Intelligent Transportation Systems. IEEE Transactions, 2002, 3: 261

[13] JiT.Y., LuZ., WuQ.H., et al.. Signal Processing, 2007, 87: 2799

[14] DuanS., QinQ.-qing.. Computer Engineering and Applications, 2007, 43: 37

[15] JiZ., BaiN., LiQ., et al.. Chinese Journal of Electronics, 2007, 16: 289

[16] NilanjanR., ScottT. A.. IEEE Transactions on Image Processing, 2005, 14: 1736