Advertisement

A general approach for extracting road vector data from raster maps

  • Yao-Yi ChiangEmail author
  • Craig A. Knoblock
Original Paper

Abstract

Raster maps are easily accessible and contain rich road information; however, converting the road information to vector format is challenging because of varying image quality, overlapping features, and typical lack of metadata (e.g., map geocoordinates). Previous road vectorization approaches for raster maps typically handle a specific map series and require significant user effort. In this paper, we present a general road vectorization approach that exploits common geometric properties of roads in maps for processing heterogeneous raster maps while requiring minimal user intervention. In our experiments, we compared our approach to a widely used commercial product using 40 raster maps from 11 sources. We showed that overall our approach generated high-quality results with low redundancy with considerably less user input compared with competing approaches.

Keywords

GIS Raster maps Road vectorization Map processing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ballard D.H.: Generalizing the hough transform to detect arbitrary shapes. Patt. Recogn. 13(2), 111–122 (1981)zbMATHCrossRefGoogle Scholar
  2. 2.
    Bin, D., Cheong, W.K.: A system for automatic extraction of road network from maps. In: Proceedings of the IEEE International Joint Symposia on Intelligence and Systems, pp. 359–366 (1998)Google Scholar
  3. 3.
    Cao, R., Tan, C.L.: Text/graphics separation in maps. In: Proceedings of the Fourth GREC, pp. 167–177 (2002)Google Scholar
  4. 4.
    Cheng H., Jiang X., Sun Y., Wang J.: Color image segmentation: advances and prospects. Patt. Recogn. 34(12), 2259–2281 (2001)zbMATHCrossRefGoogle Scholar
  5. 5.
    Chen C.-C., Knoblock C.A., Shahabi C.: Automatically and accurately conflating raster maps with orthoimagery. GeoInformatica 12(3), 377–410 (2008)CrossRefGoogle Scholar
  6. 6.
    Chen Y., Wang R., Qian J.: Extracting contour lines from common-conditioned topographic maps. IEEE Trans. Geosci. Remote Sens. 44(4), 1048–1057 (2006)CrossRefGoogle Scholar
  7. 7.
    Chiang, Y.-Y., Knoblock, C.A.: Automatic extraction of road intersection position, connectivity, and orientations from raster maps. In: Proceedings of the 16th ACM GIS, pp. 1–10 (2008)Google Scholar
  8. 8.
    Chiang, Y.-Y., Knoblock, C.A.: A method for automatically extracting road layers from raster maps. In: Proceedings of the Tenth ICDAR, pp. 838–842 (2009a)Google Scholar
  9. 9.
    Chiang Y.-Y., Knoblock C.A.: Extracting road vector data from raster maps. Select. Papers Eighth GREC LNCS 6020, 93–105 (2009)Google Scholar
  10. 10.
    Chiang Y.-Y., Knoblock C.A., Shahabi C., Chen C.-C.: Automatic and accurate extraction of road intersections from raster maps. GeoInformatica 13(2), 121–157 (2008)CrossRefGoogle Scholar
  11. 11.
    Chiang, Y.-Y., Leyl, S., Knoblock, C.A.: Integrating color image segmentation and user labeling for efficient and robust graphics recognition from historical maps. The Ninth IAPR International Workshop on Graphics Recognition (2011b)Google Scholar
  12. 12.
    Comaniciu D., Meer P.: Mean shift: a robust approach toward feature space analysis. IEEE TPAMI 24(5), 603–619 (2002)CrossRefGoogle Scholar
  13. 13.
    Duda R.O., Hart P.E.: Use of the hough transformation to detect lines and curves in pictures. Commun. ACM 15, 11–15 (1972)CrossRefGoogle Scholar
  14. 14.
    Habib, A., Uebbing, R., Asmamaw, A.: Automatic extraction of road intersections from raster maps. Project Report, Center for Mapping, The Ohio State University (1999)Google Scholar
  15. 15.
    Heckbert P.: Color image quantization for frame buffer display. SIGGRAPH 16(3), 297–307 (1982)CrossRefGoogle Scholar
  16. 16.
    Heipke, C., Mayer, H., Wiedemann, C., Jamet, O.: Evaluation of automatic road extraction. In: International Archives of Photogrammetry and Remote Sensing, pp. 47–56Google Scholar
  17. 17.
    Henderson, T.C., Linton, T., Potupchik, S., Ostanin, A.: Automatic segmentation of semantic classes in raster map images. In: Proceedings of the Eighth IAPR International Workshop on Graphics Recognition, pp. 253–262Google Scholar
  18. 18.
    Itonaga W., Matsuda I., Yoneyama N., Ito S.: Automatic extraction of road networks from map images. Electron. Commun. Jpn. 86(4), 62–72 (2003)Google Scholar
  19. 19.
    Khotanzad A., Zink E.: Contour line and geographic feature extraction from USGS color topographical paper maps. IEEE TPAMI 25(1), 18–31 (2003)CrossRefGoogle Scholar
  20. 20.
    Lacroix, V.: Automatic palette identification of colored graphics. In: Graphics Recognition: Achievements, Challenges, and Evolution, Selected Papers of the 8th International Workshop on Graphics Recognition (GREC), Lecture Notes in Computer Science, 6020, pp. 95–100. Springer, New YorkGoogle Scholar
  21. 21.
    Leyk, S., Boesch, R.: Colors of the past: color image segmentation in historical topographic maps based on homogeneity. GeoInformatica 14(1), 1–21Google Scholar
  22. 22.
    Li L., Nagy G., Samal A., Seth S.C., Xu Y.: Integrated text and line-art extraction from a topographic map. IJDAR 2(4), 177–185 (2000)CrossRefGoogle Scholar
  23. 23.
    Lloyd S.P.: Least squares quantization in pcm. IEEE Trans. Inform. Theory 28, 129–137 (1982)MathSciNetzbMATHCrossRefGoogle Scholar
  24. 24.
    Pratt W.K.: Digital Image Processing: PIKS Scientific Inside 3rd edn. Wiley, London (2001)CrossRefGoogle Scholar
  25. 25.
    Salvatore, S., Guitton, P.: Contour line recognition from scanned topographic maps. In: Proceedings of the Winter School of Computer Graphics (2004)Google Scholar
  26. 26.
    Shi, J., Tomasi, C.: Good features to track. In: Proceedings of the IEEE CVPR, pp. 593–600 (1994)Google Scholar
  27. 27.
    Tombre K., Tabbone S., Pélissier L., Lamiroy B., Dosch P.: Text/graphics separation revisited. In: Lopresti, D., Hu, J., Kashi, R. (eds) Document Analysis Systems V, vol. 2423 of Lecture Notes in Computer Science., pp. 615–620. Springer, Berlin (2002)Google Scholar
  28. 28.
    Wu, X., Carceroni, R., Fang, H., Zelinka, S., Kirmse, A.: Automatic alignment of large-scale aerial rasters to road-maps. In: Proceedings of the 15th ACM GIS, pp. 1–8 (2007)Google Scholar
  29. 29.
    Zack G., Rogers W., Latt S.: Automatic measurement of sister chromatid exchange frequency. J. Histochem. Cytochem. 25(7), 741–753 (1977)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Information Sciences Institute and Spatial Sciences InstituteUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of Computer Science and Information Sciences InstituteUniversity of Southern CaliforniaLos AngelesUSA

Personalised recommendations