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http://dx.doi.org/10.7236/IJIBC.2019.11.1.39

The Image Segmentation Method using Adaptive Watershed Algorithm for Region Boundary Preservation  

Kwon, Dong-Jin (Department of Computer Electronics Engineering, Seoil University)
Publication Information
International Journal of Internet, Broadcasting and Communication / v.11, no.1, 2019 , pp. 39-46 More about this Journal
Abstract
This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.
Keywords
Image Segmentation; Watershed Algorithm; Boundary Preservation;
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1 Jianping Fan, David. K. Y. Yau, Ahmed. K. Elmagarmid, and Walid G. Aref, "Automatic Image Segmentation by Integrating Color-Edge Extraction and Seeded Region Growing," IEEE Transaction On Image Processing, Vol. 10, No. 10, pp. 1454-1466, Oct 2001. DOI: 10.1109/83.951532   DOI
2 R. Adams, L. Bischof, "Seeded region growing," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 6, pp. 641-647, June 1994.   DOI
3 E. N. Mortensen and W. A. Barrett, "Toboggan-based Intelligent Scissors with a four-parametter edge model," in CVPR, Vol. 2, pp. 452-458, June 1999. DOI: 10.1109/CVPR.1999.784720
4 E. N. Mortensen and W. A. Barrett, "Interactive Image Segmentation with Intelligent Scissors," Graphical Models and Image Processing, Vol. 60, No. 5, pp.349-384, Sep 1998. DOI: https://doi.org/10.1006/gmip.1998.0480   DOI
5 S. Beucher and C. Lantuejoul, "Use of Watersheds in Contour Detection," Proceedings of the International workshop on Image Processing, CCETT/IRISA, pp. 17-22, Sep 1979.
6 L. Vicent and P. Soille, "Watershed in Digital Space : An Efficient Algorithm Based on Immersion Simulation," IEEE Trans. on Pattern Analysis and Machin Intelligence, Vol.13, No.6, pp. 583-598, 1991. DOI: 10.1109/34.87344   DOI
7 R.C. Gonzalez and R.E. Woods, Digital Image Processing, Prentice Hall Publishing Company, 2001.
8 S. H. Lee, "The Improved Watershed algorithm for Boundary Preservation," in Proc. KMMS, pp. 224-227, May.21-22, 2004.
9 D. J. Kwon, “The Image Segmentation Method using 2-step Thresholds Watershed Algorithm for Boundary Preservation,” The Journal of Information Technology, Vol. 13, No. 2, pp. 43-50, June 2010.