QUANTITATIVE COMPARISON OF TOLERANCE-BASED FEATURE TRANSFORMS

Dennie Reniers, Alexandru Telea

Abstract

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary images. Of these methods, the Fast Marching TFT and Euclidean TFT are new. The other two extend existing distance transform algorithms. We quantitatively and qualitatively compare all algorithms on speed and accuracy of both distance and origin results. Our analysis is aimed at helping practitioners in the field to choose the right method for given accuracy and performance constraints.

References

  1. Costa, L. and Cesar, Jr, R. (2001). Shape analysis and classification. CRC Press.
  2. Cuisenaire, O. (1999). Distance transformations: fast algorithms and applications to medical image processing. PhD thesis, Université catholique de Louvain, Belgium.
  3. Danielsson, P.-E. (1980). Euclidean distance mapping. In Computer Graphics and Image Processing, volume 14, pages 227-248.
  4. Foskey, M., Lin, M., and Manocha, D. (2003). Efficient computation of a simplified medial axis. In Proc. of the 8th ACM symposium on Solid modeling and applications, pages 96-107. ACM Press.
  5. Lotufo, T., Falcao, A., and Zampirolli, F. (2000). Fast euclidean distance transform using a graph-search algorithm. In Proc. of the 13th Brazilian Symp. on Comp. Graph. and Image Proc., pages 269-275.
  6. Meijster, A., Roerdink, J., and Hesselink, W. (2000). A general algorithm for computing distance transforms in linear time. In Goutsias, J., Vincent, L., and Bloomberg, D., editors, Mathematical Morphology and its Applications to Image and Signal Processing, pages 331-340. Kluwer.
  7. Mullikin, J. (1992). The vector distance transform in two and three dimensions. In CVGIP: Graphical Models and Image Processing, volume 54, pages 526-535. Kluwer.
  8. Musser, D. and Saini, S. (1996). STL tutorial and reference guide: C++ programming with the standard template library. Addison-Wesley Professional Computing Series.
  9. Ogniewicz, R. and Kübler, O. (1995). Hierarchic voronoi skeletons. In Pattern Recognition, volume 28, pages 343-359.
  10. Ragnemalm, I. (1992). Neighborhoods for distance transformations using ordered propagation. In CVGIP: Image Understanding, volume 56, pages 399-409.
  11. Sethian, J. (1999). Level set methods and fast marching methods. Cambridge University Press, 2nd edition.
  12. Strzodka, R. and Telea, A. (2004). Generalized distance transforms and skeletons in graphics hardware. In Proc. of EG/IEEE TCVG Symposium on Visualization (VisSym 7804), pages 221-230.
  13. Telea, A. and van Wijk, J. (2002). An augmented fast marching method for computing skeletons and centerlines. In Proc. of the symposium on Data Visualisation, pages 251-259.
  14. Telea, A. and Vilanova, A. (2003). A robust level-set algorithm for centerline extraction. In Proc. of the symposium on Data Visualisation, pages 185-194.
  15. Ye, Q. (2003). The signed euclidean distance transform and its applications. In International Conference on Pattern Recognition, volume 1, pages 495-499.
Download


Paper Citation


in Harvard Style

Reniers D. and Telea A. (2006). QUANTITATIVE COMPARISON OF TOLERANCE-BASED FEATURE TRANSFORMS . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 107-114. DOI: 10.5220/0001361801070114


in Bibtex Style

@conference{visapp06,
author={Dennie Reniers and Alexandru Telea},
title={QUANTITATIVE COMPARISON OF TOLERANCE-BASED FEATURE TRANSFORMS},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={107-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001361801070114},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - QUANTITATIVE COMPARISON OF TOLERANCE-BASED FEATURE TRANSFORMS
SN - 972-8865-40-6
AU - Reniers D.
AU - Telea A.
PY - 2006
SP - 107
EP - 114
DO - 10.5220/0001361801070114