Abstract
Lane detection in unstructured environments is the basis for navigation of mobile robots. A method for detecting lane in critical shadow conditions is proposed. Based on the color information of the unstructured lane, an improved region-growing algorithm is employed to segment the image. To enhance the image quality and the accuracy of the algorithm, a double A/D convertors camera is used to recover the color space information of the environments in critical shadow conditions. The results demonstrate that proposed method segments the lane effectively, and is robust against shadows, noises and varied illuminations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kim, Z.: Robust Lane Detection and Tracking in Challenging Scenarios. IEEE Transactions on Intelligent Transportation Systems 9, 16–26 (2008)
Mastorakis, G., Davies, E.R.: Improved Line Detection Algorithm for Locating Road Lane Markings. Electronics Letters 47, 183–184 (2011)
Nuthong, C., Charoenpong, T.: Lane Detection using Smoothing Spline. In: 2010 3rd International Congress on Image and Signal Processing (CISP), vol. 2, pp. 989–993 (2010)
Gong, J., Wang, A., Zhai, Y., Xiong, G., Zhou, P., Chen, H.: High Speed Lane Recognition under Complex Road Conditions. In: Intelligent Vehicles Symposium, pp. 566–570. IEEE Press, Los Alamitos (2008)
Jeong, P., Nedevschi, S.: Efficient and Robust Classification Method using Combined Feature Vector for Lane Detection. IEEE Transactions on Circuits and Systems for Video Technology 15, 528–537 (2005)
Asif, M., Arshad, M.R., Irfan Zia, M.Y., Yahya, A.: An Implementation of Active Contour and Kalman Filter for Road Tracking. Laeng International Journal of Applied Mathematics 37 (2007)
Cheng, H.Y., Yu, C.C., Tseng, C.C., Fan, J.C., Hwang, J.N., Jeng, B.S.: Environment Classification and Hierarchical Lane Detection for Structured and Unstructured Roads. Computer Visions 4, 37–49 (2010)
Chiu, K.-Y., Lin, S.-F.: Lane Detection using Color-based Segmentation. In: IEEE Symposium on Intelligient Vehicles, pp. 706–711. IEEE Press, Los Alamitos (2005)
Yang, B., Wang, Y., Liu, J.: HDR CCD Image Sensor System through Double-A/D Convertors. In: 2011 International Conference on Machine Learning and Artificial Intelligence (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, B., Wang, Y., Liu, J. (2011). Lane Detection in Critical Shadow Conditions Based on Double A/D Convertors Camera. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-23896-3_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23895-6
Online ISBN: 978-3-642-23896-3
eBook Packages: Computer ScienceComputer Science (R0)