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RANVEC and the Arc Segmentation Contest

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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 briefly describes an experimental arc extraction algorithm that ran the Arc Segmentation Contest at GREC’2001. As the proposed method is based on the one detailed in [5], this paper only describes the improvments we brought to the original method. We first review some rules from the evaluation protocol that helped us to make major assumptions while designing the algorithm. We then explain the method, and discuss the results we obtained in various cases. Finally, we give some conclusions and introduce a possible extension to this method.

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References

  1. G. Sanniti di Baja. Well-Shaped, Stable, and Reversible Skeletons from the (3,4)-Distance Transform. Journal of Visual Communication and Image Representation, 5(1):107–115, 1994.

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  3. http://research.microsoft.com/users/wyliu/arcsegcontest.htm.

  4. Liu Wen-Yin and Dov Dori. A Protocol for Performance Evaluation of Line Detection Algorithms. Machine Vision and Applications, Special Issue on Performance Characteristics of Vision Algorithms, 9(5/6):240–250, 1997.

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  5. Xavier HILAIRE and Karl TOMBRE. Inproving the Accuracy of Skeleton-Based Vectorization. In Proceedings of the Fourth IAPR International Workshop on Graphics Recognition, pages 381–394, 2001.

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© 2002 Springer-Verlag Berlin Heidelberg

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Hilaire, X. (2002). RANVEC and the Arc Segmentation Contest. 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_32

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  • DOI: https://doi.org/10.1007/3-540-45868-9_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44066-6

  • Online ISBN: 978-3-540-45868-5

  • eBook Packages: Springer Book Archive

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