Detection and Recognition of Road Markings in Panoramic Images

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• 作者：Cheng Li (15) (16)
  Ivo Creusen (15) (16)
  Lykele Hazelhoff (15) (16)
  Peter H. N. de With (15) (16)
  
  15. Cyclomedia Technology ; Zaltbommel ; The Netherlands
  16. Eindhoven University of Technology ; Eindhoven ; The Netherlands
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9009
• 期：1
• 页码：448-458
• 全文大小：6,132 KB
• 参考文献：1. McCall, J, Trivedi, M (2006) Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation. IEEE Trans. Intell. Transp. Syst. 7: pp. 20-37 CrossRef
  2. Rebut, J., Bensrhair, A., Toulminet, G.: Image segmentation and pattern recognition for road marking analysis. In: IEEE International Symposium on Industrial Electronics, vol. 1, pp. 727鈥?32 (2004)
  3. Maeda, T., Hu, Z., Wang, C., Uchimura, K.: High-speed lane detection for road geometry estimation and vehicle localization. In: SICE Annual Conference, 2008, pp. 860鈥?65 (2008)
  4. Kreucher, C, Lakshmanan, S (1999) Lana: a lane extraction algorithm that uses frequency domain features. IEEE Trans. Rob. Autom. 15: pp. 343-350 CrossRef
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  6. Kheyrollahi, A, Breckon, T (2012) Automatic real-time road marking recognition using a feature driven approach. Mach. Vis. Appl. 23: pp. 123-133 CrossRef
  7. Noda, M., Takahashi, T., Deguchi, D., Ide, I., Murase, H., Kojima, Y., Naito, T.: Recognition of road markings from in-vehicle camera images by a generative learning method. In: Proceedings of the IAPR Conference on Machine Vision Applications (2009)
  8. Wu, T., Ranganathan, A.: A practical system for road marking detection and recognition. In: Intelligent Vehicles Symposium (IV), pp. 25鈥?0. IEEE (2012)
  9. Foucher, P., Sebsadji, Y., Tarel, J.P., Charbonnier, P., Nicolle, P.: Detection and recognition of urban road markings using images. In: 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1747鈥?752 (2011)
  10. Wang, Y, Shen, D, Teoh, EK (2000) Lane detection using spline model. Pattern Recogn. Lett. 21: pp. 677-689 CrossRef
  11. Vapnik, VN (1995) The Nature of Statistical Learning Theory. Springer, New York CrossRef
  
• 作者单位：Computer Vision - ACCV 2014 Workshops
• 丛书名：978-3-319-16630-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

The detection of road lane markings has many practical applications, such as advanced driver assistance systems and road maintenance. In this paper we propose an algorithm to detect and recognize road lane markings from panoramic images. Our algorithm consists of four steps. First, an inverse perspective mapping is applied to the image, and the potential road markings are segmented based on their intensity difference compared to the surrounding pixels. Second, we extract the distance between the center and the boundary at regular angular steps of each considered potential road marking segment into a feature vector. Third, each segment is classified using a Support Vector Machine (SVM). Finally, by modeling the lane markings, previous false positive detected segments can be rejected based on their orientation and position relative to the lane markings. Our experiments show that the system is capable of recognizing \(93\,\%\) , \(95\,\%\) and \(91\,\%\) of striped line segments, blocks and arrows respectively, as well as \(94\,\%\) of the lane markings.