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Journal of Sensors
Volume 2015, Article ID 784504, 13 pages
http://dx.doi.org/10.1155/2015/784504
Research Article

Use of GMM and SCMS for Accurate Road Centerline Extraction from the Classified Image

1Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong
2School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China
3School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan, Hubei 430079, China

Received 29 August 2014; Revised 22 October 2014; Accepted 23 October 2014

Academic Editor: Yongqiang Zhao

Copyright © 2015 Zelang Miao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. B. Mena, “State of the art on automatic road extraction for GIS update: a novel classification,” Pattern Recognition Letters, vol. 24, no. 16, pp. 3037–3058, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. S. Das, T. T. Mirnalinee, and K. Varghese, “Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 10, pp. 3906–3931, 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, “Spectral-spatial classification of hyperspectral imagery based on partitional clustering techniques,” IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 8, pp. 2973–2987, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Fauvel, Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, “Advances in spectral-spatial classification of hyperspectral images,” Proceedings of the IEEE, vol. 101, no. 3, pp. 652–675, 2013. View at Publisher · View at Google Scholar · View at Scopus
  5. M. Song and D. Civco, “Road extraction using SVM and image segmentation,” Photogrammetric Engineering and Remote Sensing, vol. 70, no. 12, pp. 1365–1371, 2004. View at Publisher · View at Google Scholar · View at Scopus
  6. Z. Miao, W. Shi, H. Zhang, and X. Wang, “Road centerline extraction from high-resolution imagery based on shape features and multivariate adaptive regression splines,” IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 3, pp. 583–587, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Huang and L. Zhang, “Road centreline extraction from high-resolution imagery based on multiscale structural features and support vector machines,” International Journal of Remote Sensing, vol. 30, no. 8, pp. 1977–1987, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. W. Shi, Z. Miao, and J. Debayle, “An integrated method for urban main-road centerline extraction from optical remotely sensed imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 6, pp. 3359–3372, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Valero, J. Chanussot, J. A. Benediktsson, H. Talbot, and B. Waske, “Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images,” Pattern Recognition Letters, vol. 31, no. 10, pp. 1120–1127, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. W. Shi, Z. Miao, Q. Wang, and H. Zhang, “Spectral-spatial classification and shape features for urban road centerline extraction,” IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 4, pp. 788–792, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Q. Zhao and J. Yang, “Hyperspectral image denoising via sparse representation and low-rank constraint,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 1, pp. 296–308, 2015. View at Publisher · View at Google Scholar
  12. Y.-Q. Zhao, L. Zhang, and S. G. Kong, “Band-subset-based clustering and fusion for hyperspectral imagery classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 2, pp. 747–756, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. D. Chaudhuri, N. K. Kushwaha, and A. Samal, “Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 5, pp. 1538–1544, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. D. Guo, A. Weeks, and H. Klee, “Robust approach for suburban road segmentation in high-resolution aerial images,” International Journal of Remote Sensing, vol. 28, no. 2, pp. 307–318, 2007. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Mohammadzadeh and M. J. V. Zoej, “A Self-Organizing Fuzzy Segmentation (SOFS) method for road detection from high resolution satellite images,” Photogrammetric Engineering and Remote Sensing, vol. 76, no. 1, pp. 27–35, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. W. Wei and Y. Xin, “Feature extraction for man-made objects segmentation in aerial images,” Machine Vision and Applications, vol. 19, no. 1, pp. 57–64, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. I. Laptev, H. Mayer, T. Lindeberg, W. Eckstein, C. Steger, and A. Baumgartner, “Automatic extraction of roads from aerial images based on scale space and snakes,” Machine Vision and Applications, vol. 12, no. 1, pp. 23–31, 2000. View at Publisher · View at Google Scholar · View at Scopus
  18. L. Bentabet, S. Jodouin, D. Ziou, and J. Vaillancourt, “Road vectors update using SAR imagery: a snake-based method,” IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 8, pp. 1785–1803, 2003. View at Publisher · View at Google Scholar · View at Scopus
  19. K. Karantzalos and D. Argialas, “A region-based level set segmentation for automatic detection of man-made objects from aerial and satellite images,” Photogrammetric Engineering and Remote Sensing, vol. 75, no. 6, pp. 667–677, 2009. View at Publisher · View at Google Scholar · View at Scopus
  20. M. Rochery, I. H. Jermyn, and J. Zerubia, “Higher order active contours,” International Journal of Computer Vision, vol. 69, no. 1, pp. 27–42, 2006. View at Publisher · View at Google Scholar · View at Scopus
  21. R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital Image Processing Using MATLAB, Prentice-Hall, 2003.
  22. P. Doucette, P. Agouris, A. Stefanidis, and M. Musavi, “Self-organised clustering for road extraction in classified imagery,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 55, no. 5-6, pp. 347–358, 2001. View at Publisher · View at Google Scholar · View at Scopus
  23. C. Poullis and S. You, “Delineation and geometric modeling of road networks,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 65, no. 2, pp. 165–181, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. Q. Zhang and I. Couloigner, “Accurate centerline detection and line width estimation of thick lines using the radon transform,” IEEE Transactions on Image Processing, vol. 16, no. 2, pp. 310–316, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  25. U. Ozertem and D. Erdogmus, “Nonparametric snakes,” IEEE Transactions on Image Processing, vol. 16, no. 9, pp. 2361–2368, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. U. Ozertem and D. Erdogmus, “Principal curve time warping,” IEEE Transactions on Signal Processing, vol. 57, no. 6, pp. 2041–2049, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  27. U. Ozertem and D. Erdogmus, “Locally defined principal curves and surfaces,” Journal of Machine Learning Research, vol. 12, pp. 1249–1286, 2011. View at Google Scholar · View at MathSciNet · View at Scopus
  28. Z. Miao, B. Wang, W. Shi, and H. Wu, “A method for accurate road centerline extraction from a classified image,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014. View at Publisher · View at Google Scholar
  29. S. Movaghati, A. Moghaddamjoo, and A. Tavakoli, “Road extraction from satellite images using particle filtering and extended Kalman filtering,” IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 7, pp. 2807–2817, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Hu, A. Razdan, J. C. Femiani, M. Cui, and P. Wonka, “Road network extraction and intersection detection from aerial images by tracking road footprints,” IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 12, pp. 4144–4157, 2007. View at Publisher · View at Google Scholar · View at Scopus
  31. A. P. Dal Poz, R. A. B. Gallis, J. F. C. da Silva, and É. F. O. Martins, “Object-space road extraction in rural areas using stereoscopic aerial images,” IEEE Geoscience and Remote Sensing Letters, vol. 9, no. 4, pp. 654–658, 2012. View at Publisher · View at Google Scholar · View at Scopus
  32. F. Dell'Acqua and P. Gamba, “Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking,” IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 10, pp. 2287–2297, 2001. View at Publisher · View at Google Scholar · View at Scopus
  33. M. Negri, P. Gamba, G. Lisini, and F. Tupin, “Junction-aware extraction and regularization of urban road networks in high-resolution SAR images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 10, pp. 2962–2971, 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. Y.-W. Choi, Y.-W. Jang, H.-J. Lee, and G.-S. Cho, “Three-Dimensional LiDAR data classifying to extract road point in urban area,” IEEE Geoscience and Remote Sensing Letters, vol. 5, no. 4, pp. 725–729, 2008. View at Publisher · View at Google Scholar · View at Scopus
  35. S. Clode, F. Rottensteiner, P. Kootsookos, and E. Zelniker, “Detection and vectorization of roads from lidar data,” Photogrammetric Engineering and Remote Sensing, vol. 73, no. 5, pp. 517–535, 2007. View at Publisher · View at Google Scholar · View at Scopus
  36. P. Kumar, C. P. McElhinney, P. Lewis, and T. McCarthy, “An automated algorithm for extracting road edges from terrestrial mobile LiDAR data,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 85, pp. 44–55, 2013. View at Publisher · View at Google Scholar · View at Scopus
  37. R. B. Gomez, “Hyperspectral imaging: a useful technology for transportation analysis,” Optical Engineering, vol. 41, no. 9, pp. 2137–2143, 2002. View at Publisher · View at Google Scholar · View at Scopus
  38. S. Roessner, K. Segl, U. Heiden, and H. Kaufmann, “Automated differentiation of urban surfaces based on airborne hyperspectral imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 7, pp. 1525–1532, 2001. View at Publisher · View at Google Scholar · View at Scopus
  39. I. Ahamada and E. Flachaire, Non-Parametric Econometrics, Oxford University Press, Oxford, UK, 2010.
  40. C. Wiedemann, C. Heipke, and H. Mayer, “Empirical evaluation of automatically extracted road axes,” in Proceedings of the CVPR Workshop on Empirical Evaluation Techniques in Computer Vision, Los Alamitos, Calif, USA, 1998.