Abstract
In this paper we present a new implementation of a rainfalling watershed segmentation algorithm. Our previous algorithm was a one-run algorithm. All the steps needed to compute a complete watershed segmentation were done in one run over the input data. In our new algorithm we tried another approach. We separated the watershed algorithm in several low-complexity relabeling steps that can be performed sequentially on a label image. The new implementation is approximately two times faster for parameters that produce visually good segmentations. The new algorithm also handles plateaus in a better way. First we describe the general layout of a rainfalling watershed algorithm. Then we explain the implementations of the two algorithms. Finally we give a detailed report on the timings of the two algorithms for different parameters.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Vincent, L., Soille, P.: Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence 13, 583–598 (1991)
Soille, P.: Morphological Image Analysis: Principles and Applications. Springer, Heidelberg (1999)
Beucher, S.: Segmentation d’images et morphologie mathématique. PhD thesis, School of Mines (1990)
Moga, A., Cramariuc, B., Gabbouj, M.: A parallel watershed algorithm based on rainfalling simulation. In: Proc. 12th European Conf. Circuit Theory and Design., vol. 1, pp. 339–342 (1995)
De Smet, P., Pires, R.: Implementation and analysis of an optimized rainfalling watershed algorithm. In: Proc. Electronic Imaging, Science and Technology, Image and Video Communications and Processing, pp. 759–766 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
De Bock, J., De Smet, P., Philips, W. (2005). A Fast Sequential Rainfalling Watershed Segmentation Algorithm. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_60
Download citation
DOI: https://doi.org/10.1007/11558484_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29032-2
Online ISBN: 978-3-540-32046-3
eBook Packages: Computer ScienceComputer Science (R0)