Skip to main content

A Method of Coastline Detection from High-Resolution Remote Sensing Images Based on the Improved Snake Model

  • Conference paper
  • First Online:
3rd International Symposium of Space Optical Instruments and Applications

Part of the book series: Springer Proceedings in Physics ((SPPHY,volume 192))

  • 1226 Accesses

Abstract

While executing tasks such as ocean pollution monitoring, maritime rescue, geographic mapping, ship localization, cruise missile guidance and automatic navigation utilizing remote sensing images, the coastline feature should be determined. Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image. Active contour model, also called snakes, have proven useful for interactive specification of image contours, so it is used as an effective coastlines extraction technique. Firstly, coastlines are detected by water segmentation and boundary tracking, which are considered initial contours to be optimized through active contour model. As better energy functions are developed, the power assist of snakes becomes effective. New internal energy has been done to reduce problems caused by convergence to local minima, and new external energy can greatly enlarge the capture region around features of interest. After normalization processing, energies are iterated using greedy algorithm to accelerate convergence rate. The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Niedermeier A, Romaneeen E, Lehner S. Detection of coastlines in SAR Images using wavelet method. IEEE Trans. on Geoscience and Remote Sensing, 2000. 38(5): 2270–2281.

    Google Scholar 

  2. Karantzalos K G, Argialas D, Georgopoulos A. Towards automatic detection of coastlines from satellite imagery. In: Proceedings of 14th International Conference on Digital Signal Processing, Santorini, Greece, 2002(2). 897–900.

    Google Scholar 

  3. Lu Liming, Wang Runsheng, Li Wugao. A method of coastline extraction from synthetic aperture radar raw-data. Journal of Software, 2004, 16(6): 531–53.

    Google Scholar 

  4. Frazier P S, Page K J, Water body detection and delineation with Landsat TM data. Photogrammetric. Engineering and remote sensing, 2000, 66(12): 1461–1467.

    Google Scholar 

  5. Kevin W, Elasmar H M. Monitoring changing position of coastlines using thematic mapper imagery, an example from the Nile Delta. Geomorphology, 1999, 29(1–2): 93–105.

    Google Scholar 

  6. Jing Hao, Chen Xuequan, Gu Zhiwei. A method for coastline extraction based on edges. Computer simulation, 2006, 23(8): 89–93.

    Google Scholar 

  7. Kass M, Witkin A, Terzopoulos D. Snakes: Active contour models. International Journal of Computer Vision, 1987, 1(4): 321–331.

    Google Scholar 

  8. Li Peihua, Zhang Tianwen. Review on active contour model(Snake model). Journal of Software, 2000, 11(6):751–757.

    Google Scholar 

  9. Cohen L D, Cohen I. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1993, 15(11): 1131–1147.

    Google Scholar 

  10. Xu C, Prince J L. Snakes, shapes, and gradient vector flow. IEEE Trans. on Image Processing, 1998, 7(3): 359–369.

    Google Scholar 

  11. Williams D J, Shah M. A fast algorithm for active contours and curvature estimation. CVGIP: Image Understanding, 1992, 55(1): 14–26.

    Google Scholar 

  12. Wang X N, Feng Y J, Feng Z R. Ant colony optimization for image segmentation. In: Proceedings of the 4th International Conference on Machine Learning and Cybernetics, Guangzhou, China, 2005, 5355–5360.

    Google Scholar 

  13. Oliveira A, Ribeiro S, Esperanca C, Giraldi G. Loop snakes: the generalized model. In: Proceedings of the 9th International Conference on Information Visualisation, Washington, DC, USA, 2005, 975–980.

    Google Scholar 

  14. Pal S K. Automatic graylevel thresholding through index of fuzziness entropy. Pattern Recognition Letters, 1983(1): 141–146.

    Google Scholar 

  15. Wu Fan, Wang Chao, Zhang Hong, Zhang Bo, Zhang Wei-sheng. Knowledge-based bridge recognition in high resolution optical imagery. Journal of Electronics & Information Technology, 2006, 28(4):587–591.

    Google Scholar 

  16. Amini A A, Tehrani S, Weymouth T E. Using dynamic programming for minimizing the energy of active contours in the presence of hard constraints. In: Proceedings of 2nd Int. Conf. Computer Vision, Los Alamitos, CA, USA, 1988, 95–99.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xing Kun .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Kun, X., Bing-xian, Z., Hong-yan, H. (2017). A Method of Coastline Detection from High-Resolution Remote Sensing Images Based on the Improved Snake Model. In: Urbach, H., Zhang, G. (eds) 3rd International Symposium of Space Optical Instruments and Applications. Springer Proceedings in Physics, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-319-49184-4_41

Download citation

Publish with us

Policies and ethics