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International Workshop on Graphics Recognition

GREC 1999: Graphics Recognition Recent Advances pp 3–18Cite as

Stable and Robust Vectorization: How to Make the Right Choices

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1941))

Abstract

As a complement to quantitative evaluation methods for raster-to-graphics conversion, we discuss in this paper some qualitative elements which should be taken into account when choosing the different steps of one’s vectorization method. We stress the importance of having robust methods and stable implementations, and we base ourselves extensively on our own implementations and tests, concentrating on methods designed to have few, if any, parameters.

This work was partly funded by France Telecom CNET.

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Author information

Authors and Affiliations

  1. LORIA, B.P. 239, 54506, Vandœuvre-lès-Nancy CEDEX, France

    Karl Tombre, Christian Ah-Soon, Philippe Dosch, Gérald Masini & Salvatore Tabbone

Authors
  1. Karl Tombre
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  2. Christian Ah-Soon
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  3. Philippe Dosch
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  4. Gérald Masini
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  5. Salvatore Tabbone
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Editor information

Editors and Affiliations

  1. Verizon Communications, 500 Westchester Avenue, White Plains, 10604, NY, USA

    Atul K. Chhabra

  2. School of Engineering, Engineering Systems Division, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139-4307, USA

    Dov Dori

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© 2000 Springer-Verlag Berlin Heidelberg

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Tombre, K., Ah-Soon, C., Dosch, P., Masini, G., Tabbone, S. (2000). Stable and Robust Vectorization: How to Make the Right Choices. In: Chhabra, A.K., Dori, D. (eds) Graphics Recognition Recent Advances. GREC 1999. Lecture Notes in Computer Science, vol 1941. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40953-X_1

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  • DOI: https://doi.org/10.1007/3-540-40953-X_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41222-9

  • Online ISBN: 978-3-540-40953-3

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