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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 212))

Abstract

The watershed transformation is a kind of powerful morphological tool for image segmentation, which can automatically segment images into a series of closed segmentation regions. Fracture image of great amount of information is an important basis for clinical diagnosis. This thesis is about the segmentation to the fracture image by dint of watershed transformation. However, fracture images are often mixed with noise and uneven distribution, direct application of watershed transformation will have a serious over segmentation. Over segmentation phenomenon can be curbed by markers-controlled watershed algorithm in some extent, but this segmentation algorithm is not universal. In this paper, we introduce the morphological direction gradient and marker selection algorithm based the on marker-controlled watershed algorithm. And then we propose an improved watershed algorithm. We evaluate the proposed algorithm by simulation experiment through MATLAB. The experiments’ result shows that the improved watershed algorithm can prevent over-segmentation effectively and extract the target bone edge from fracture images accurately.

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Acknowledgments

This work is sponsored by the 382 Talents Plan (G08382304), Chinese National Hi-tech Industrialzation Project(CNGI-09-03-15-1), and the Virtual Library Technology project granted by China Art Science and Technology Institute.

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Correspondence to Bingren Sun .

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© 2013 Springer-Verlag Berlin Heidelberg

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Sun, B., Cao, S. (2013). Research of Image Segmentation Based on Watershed Transformation. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34531-9_85

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  • DOI: https://doi.org/10.1007/978-3-642-34531-9_85

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34530-2

  • Online ISBN: 978-3-642-34531-9

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