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A Lane Detection Algorithm Based on Hyperbola Model

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Computer Engineering and Networking

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 277))

Abstract

In order to improve the problem of recognition rate and inaccurate in the curve, this paper proposed a lane detection algorithm based on hyperbola model, which uses Canny operator to detect the edge of the lane and wields the Hough transform to extract lane boundary points, and utilizes extended Kalman filter to reduce road scanning range. By fitting points on pair road boundaries into the hyperbola model, and completes the lane boundary reconstruction. Some experimental studies are conducted, and the results show that the accuracy of the algorithm has reached 93.4 % and the processing speed of each image needs 77.4 ms. Our method is able to make full use of lane boundaries with existence partial occlusion, blur and low contrast. Meanwhile, it can quickly and accurately identify lane line, and it has high performance and robustness.

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References

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Acknowledgements

This work was supported by the projection of National Natural Science Foundation of China (61271362) and Shaanxi Province Natural Science Foundation (12JK0502). We would like to thank them.

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Correspondence to Song Gao .

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© 2014 Springer International Publishing Switzerland

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Chen, C., Zhang, B., Gao, S. (2014). A Lane Detection Algorithm Based on Hyperbola Model. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_70

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  • DOI: https://doi.org/10.1007/978-3-319-01766-2_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01765-5

  • Online ISBN: 978-3-319-01766-2

  • eBook Packages: EngineeringEngineering (R0)

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