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Real-time illumination and shadow invariant lane detection on mobile platform

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Abstract

In this work, a novel lane detection method using a single input image is presented. The proposed method adopts a color and shadow invariant preprocessing stage including a feature region detection method called as maximally stable extremal regions. Next, candidate lane regions are examined according to their structural properties such as width–height ratio and orientation. This stage is followed by a template matching-based approach to decide final candidates for lane markings. At the final stage of the proposed method, outliers are eliminated using the random sample consensus approach. The proposed method is computationally lightweight, and thus, it is possible to execute it in real-time on consumer-grade mobile devices. Experimental results show that the proposed method is able to provide shadow, illumination and road defects invariant performance compared to the existing methods.

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Acknowledgements

Authors would like to thank the editor and reviewers for their constructive recommendations which we believe have improved the understanding and representation of the paper. Authors also would like to thank M. Torres-Torriti for sharing their implementation and A. Borkar and H. Ocak for helping the implementation of their methods.

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Authors and Affiliations

  1. Electronics and Telecommunication Engineering Department, University of Kocaeli, Kocaeli, Turkey

    Ayhan Küçükmanisa, Gökhan Tarım & Oğuzhan Urhan

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  1. Ayhan Küçükmanisa
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  2. Gökhan Tarım
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  3. Oğuzhan Urhan
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Correspondence to Oğuzhan Urhan.

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Küçükmanisa, A., Tarım, G. & Urhan, O. Real-time illumination and shadow invariant lane detection on mobile platform. J Real-Time Image Proc 16, 1781–1794 (2019). https://doi.org/10.1007/s11554-017-0687-2

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  • DOI: https://doi.org/10.1007/s11554-017-0687-2

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