Abstract
We propose a novel approach for solving the over-segmentation problem in image segmentation. Rather than focusing on clustering gray pixels in the image data, our approach aims at extracting salient regions based on edges information. We treat image segmentation as an edge linking problem and propose a novel process, edge growth, for segmenting the image. The edge growth process is starting from the breakpoints and then prolongs the edge chains based on its local structure until there is another breakpoint or edges. We have applied this approach to segmenting static images without tuning any parameters. The experimental result shows the effective of our proposed algorithm.
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Acknowledgments
The research was supported by NSFC (61005034, 60905046) and the natural science foundation of Hebei Province (F2012203185, F2012203182).
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Cao, X., Ding, W., Hu, S., Su, L. (2013). Image Segmentation Based on Edge Growth. 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_57
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DOI: https://doi.org/10.1007/978-3-642-34531-9_57
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