Abstract
The region growing paradigm is a well known technique for image segmentation. In the first part of this work, the robustness of region growing algorithms is studied. It is shown that within a small parameter range, which leads to good segmentation results in the majority of cases, bad segmentation results may occur. Furthermore the influence of noise on segmentation results is studied. In fact, instability is a problem of region growing methods and reasons for its occurrence are discussed. In the second part of the work, a solution for this problem based on the set median concept is proposed. The set median is adopted to combine image ensembles and stability is achieved. Experimental results illustrate the performance of our approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Deng, Y., Manjunath, B.S.: Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. Pattern Analysis and Machine Intelligence 23, 800–810 (2001)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. Int. J. Computer Vision 59, 167–181 (2004)
Wan, S.Y., Higgins, W.E.: Symmetric region growing. IEEE Trans. Image Process 12, 1007–1015 (2003)
Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proc. ICCV, vol. 2, pp. 416–423 (2001)
Martin, D., Fowlkes, C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. Pattern Anal. Machine Intell 26, 530–539 (2004)
Strehl, A., Ghosh, J.: Cluster ensembles - a knowledge reuse framework for combining multiple partitions. J. on Machine Learning Research 3, 583–617 (2002)
Priese, L., Rehrmann, V.: A fast hybrid color segmentation method. In: Proceedings Mustererkennung, DAGM Symposium 1993, pp. 297–304. Springer, Heidelberg (1993)
Adams, R., Bischof, L.: Seeded region growing. IEEE Trans. Pattern Anal. Mach. Intell. 16(6), 641–647 (1994)
Wattuya, P., Jiang, X.: Ensemble combination for solving the parameter selection problem in image segmentation. In: da Vitoria Lobo, N., Kasparis, T., Roli, F., Kwok, J.T., Georgiopoulos, M., Anagnostopoulos, G.C., Loog, M. (eds.) S+SSPR 2008. LNCS, vol. 5342, pp. 392–401. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Franek, L., Jiang, X. (2009). An Instability Problem of Region Growing Segmentation Algorithms and Its Set Median Solution. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_70
Download citation
DOI: https://doi.org/10.1007/978-3-642-10520-3_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10519-7
Online ISBN: 978-3-642-10520-3
eBook Packages: Computer ScienceComputer Science (R0)