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Smoothing and Compression of Lines Obtained by Raster-to-Vector Conversion

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Graphics Recognition Algorithms and Applications (GREC 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2390))

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Abstract

This paper presents analyses of different methods of postprocessing lines that have resulted from the raster-to-vector conversion of black and white line drawing. Special attention was paid to the borders of connected components of maps. These methods are implemented with compression and smoothing algorithms. Smoothing algorithms can enhance accuracy, so using both smoothing and compression algorithms in succession gives a more accurate result than using only a compression algorithm. The paper also shows that a map in vector format may require more memory than a map in raster format. The Appendix contains a detailed description of the new smoothing method (continuous local weighted averaging) suggested by the authors.

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References

  1. Bodansky, E., Pilouk, M.: Using Local Deviations of Vectorization to Enhance the Performance of Raster-to-Vector Conversion Systems. IJDAR, Vol. 3, #2 (2000) 67–72.

    Article  Google Scholar 

  2. Quek, F.: An algorithm for the rapid computation of boundaries of run-length encoded regions. Pattern Recognition, 33 (2000) 1637–1649.

    Article  Google Scholar 

  3. Ablameyko, S., Pridmore, T.: Machine Interpretation of Line Drawing Images. (Technical Drawings, Maps, and Diagrams.) Springer (2000).

    Google Scholar 

  4. Douglas, D., Peucker, Th.: Algorithm for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer, Vol. 10, #2 (1973) 112–122.

    Google Scholar 

  5. Ramer, U.: Extraction of Line Structures from Photographs of Curved Objects. Computer Graphics and Image Processing. Vol. 4 (1975) 81–103.

    Article  Google Scholar 

  6. Sklansky, J., Gonzalez, V.: Fast Polygonal Approximation of Digitized Curves. Pattern Recognition, Vol. 12 (1980) 327–331.

    Article  Google Scholar 

  7. Curozumi, Y., Davis, W.: Polygonal approximation by minimax method.” Computer Graphics and Image Processing, Vol. 19 (1982) 248–264.

    Article  Google Scholar 

  8. R.B. McMaster Automated line generalization. Cartographica, Vol. 24, #2, 1987, pp. 74–111.

    MathSciNet  Google Scholar 

  9. E.R. White. ”Assessment of line-generalization algorithms using characteristic points.” American Cartographer, Vol. 12, #1, 1985, pp. 17–27.

    Google Scholar 

  10. H. Asada, M. Brady. “The curvature primal sketch.” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, #1, 1986, pp. 2–14.

    Article  Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Bodansky, E., Gribov, A., Pilouk, M. (2002). Smoothing and Compression of Lines Obtained by Raster-to-Vector Conversion. In: Blostein, D., Kwon, YB. (eds) Graphics Recognition Algorithms and Applications. GREC 2001. Lecture Notes in Computer Science, vol 2390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45868-9_22

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  • DOI: https://doi.org/10.1007/3-540-45868-9_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44066-6

  • Online ISBN: 978-3-540-45868-5

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