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.
Keywords
- Compression Algorithm
- Smoothing Method
- Smoothing Algorithm
- Raster Image
- Polygonal Approximation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Buying options
Preview
Unable to display preview. Download preview PDF.
References
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.
Quek, F.: An algorithm for the rapid computation of boundaries of run-length encoded regions. Pattern Recognition, 33 (2000) 1637–1649.
Ablameyko, S., Pridmore, T.: Machine Interpretation of Line Drawing Images. (Technical Drawings, Maps, and Diagrams.) Springer (2000).
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.
Ramer, U.: Extraction of Line Structures from Photographs of Curved Objects. Computer Graphics and Image Processing. Vol. 4 (1975) 81–103.
Sklansky, J., Gonzalez, V.: Fast Polygonal Approximation of Digitized Curves. Pattern Recognition, Vol. 12 (1980) 327–331.
Curozumi, Y., Davis, W.: Polygonal approximation by minimax method.” Computer Graphics and Image Processing, Vol. 19 (1982) 248–264.
R.B. McMaster Automated line generalization. Cartographica, Vol. 24, #2, 1987, pp. 74–111.
E.R. White. ”Assessment of line-generalization algorithms using characteristic points.” American Cartographer, Vol. 12, #1, 1985, pp. 17–27.
H. Asada, M. Brady. “The curvature primal sketch.” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, #1, 1986, pp. 2–14.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/3-540-45868-9_22
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44066-6
Online ISBN: 978-3-540-45868-5
eBook Packages: Springer Book Archive