Abstract
Multi-resolution methods applied to active contour models can speed up processes and improve results. In order to estimate those improvements, we describe and compare in this paper two models using such algorithms. First we propose a multi-resolution algorithm of an improved snake model, the balloon model. Convergence is achieved on an image pyramid and parameters are automatically modified so that, at each scale, the maximal length of the curve is proportional to the image size. This algorithm leads to an important saving in computational time without decreasing the accuracy of the result at the full scale. Then we present a multi-resolution parametrically deformable model using Fourier descriptors in which the curve is first described by a single harmonic; then harmonics of higher frequencies are used so that precision increases with the resolution. We show that boundary finding using this multi-resolution algorithm leads to more stability. These models illustrate two different ways of using multi-resolution methods: the first one uses multi-resolution data, the second one applies multi-resolution to the model itself.
Preview
Unable to display preview. Download preview PDF.
References
M. O. Berger and R. Mohr. Towards autonomy in active contour models. In Proceedings of the International Conference of Pattern Recognition, pages 847–851, Atlantic City, NJ, June 1990.
L. D. Cohen. On active contour models and balloons. CVGIP: Graphical models and Image Processing, 53(2):211–218, March 1991.
L. D. Cohen and I. Cohen. Finite element methods for active contour models and balloons for 2-D and 3-D images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11):1131–1147, November 1993.
L. D. Cohen and A. Gorre. On the convexity of the active contour energy. In Proceedings of GRETSI, Juan-les-Pins, September 1995.
K. Deng and J. N. Wilson. Contour estimation using global shape constraints and local forces. In Proceedings of SPIE, Geometric Methods in Computer Vision, volume 1570, pages 1–7, San Diego, California, U.S.A., July 1991.
M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. In IEEE Proceedings of the International Conference on Computer Vision, pages 259–268, London, June 1987.
B. Leroy, A. Chouakria, I. L. Herlin, and E. Diday. Approche géométrique et classification pour la reconnaissance de visage. In Congrès Reconnaissance des Formes et Intelligence Artificielle, Rennes, January 1996.
F. Leymarie and M. Levine. Tracking deformable objects in the plane using an active contour model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):635–646, 1993.
L. H. Staib and J. S. Duncan. Boundary finding with parametrically deformable models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(11):1061–1075, November 1992.
Demetri Terzopoulos. Multiresolution algorithms in computational vision. In Image Understanding, pages 225–262. S.Ullman, W.Richards, 1986.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag London Limited
About this paper
Cite this paper
Leroy, B., Herlin, I.L., Cohen, L.D. (1996). Multi-resolution algorithms for active contour models. In: Berger, MO., Deriche, R., Herlin, I., Jaffré, J., Morel, JM. (eds) ICAOS '96. Lecture Notes in Control and Information Sciences, vol 219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-76076-8_117
Download citation
DOI: https://doi.org/10.1007/3-540-76076-8_117
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76076-4
Online ISBN: 978-3-540-40945-8
eBook Packages: Springer Book Archive