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2017 | OriginalPaper | Buchkapitel

Image Segmentation Based on Solving the Flow in the Mesh with the Connections of Limited Capacities

verfasst von : Michael Holuša, Andrey Sukhanov, Eduard Sojka

Erschienen in: Image Analysis and Recognition

Verlag: Springer International Publishing

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Abstract

This paper presents a novel seeded segmentation technique inspired by the flowing of a liquid in a mesh of pipes. The method can be likened to the anisotropic diffusion algorithm. On the other hand, some substantial changes in the relation of how the diffusion works are included. The method is based on the spreading of liquid from the foreground seeds to the neighboring image points that represent basins with an initial amount of liquid. The background seeds drain the liquid from the neighboring basins. If a basin is full or empty, the corresponding pixel becomes a new source or sink. The algorithm runs until all pixels become either sources or sinks. The properties of the method are illustrated on the image segmentation of synthetic images. The comparison with other segmentation techniques is presented on real-life images. The experiments show promising results of the new method.

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Literatur
1.
Zurück zum Zitat Bleau, A., Leon, L.: Watershed-based segmentation and region merging. Comput. Vis. Image Underst. 77(3), 317–370 (2000)CrossRef Bleau, A., Leon, L.: Watershed-based segmentation and region merging. Comput. Vis. Image Underst. 77(3), 317–370 (2000)CrossRef
2.
Zurück zum Zitat Boykov, Y., Jolly, M.P.: Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In: Proceedings of the 8th IEEE International Conference on Computer Vision, ICCV 2001, vol. 1, pp. 105–112 (2001) Boykov, Y., Jolly, M.P.: Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In: Proceedings of the 8th IEEE International Conference on Computer Vision, ICCV 2001, vol. 1, pp. 105–112 (2001)
3.
Zurück zum Zitat Collins, M.D., Xu, J., Grady, L., Singh, V.: Random walks based multi-image segmentation: quasiconvexity results and GPU-based solutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012) Collins, M.D., Xu, J., Grady, L., Singh, V.: Random walks based multi-image segmentation: quasiconvexity results and GPU-based solutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012)
4.
Zurück zum Zitat Gopalakrishnan, V., Hu, Y., Rajan, D.: Random walks on graphs for salient object detection in images. IEEE Trans. Image Process. 19(12), 3232–3242 (2010)MathSciNetCrossRef Gopalakrishnan, V., Hu, Y., Rajan, D.: Random walks on graphs for salient object detection in images. IEEE Trans. Image Process. 19(12), 3232–3242 (2010)MathSciNetCrossRef
5.
Zurück zum Zitat Grady, L.: Random walks for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1768–1783 (2006)CrossRef Grady, L.: Random walks for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1768–1783 (2006)CrossRef
6.
Zurück zum Zitat Lee, C., Jang, W.D., Sim, J.Y., Kim, C.S.: Multiple random walkers and their application to image cosegmentation. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3837–3845 (2015) Lee, C., Jang, W.D., Sim, J.Y., Kim, C.S.: Multiple random walkers and their application to image cosegmentation. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3837–3845 (2015)
7.
Zurück zum Zitat Lee, S.H., Jang, W.D., Park, B.K., Kim, C.S.: RGB-D image segmentation based on multiple random walkers. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 2549–2553 (2016) Lee, S.H., Jang, W.D., Park, B.K., Kim, C.S.: RGB-D image segmentation based on multiple random walkers. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 2549–2553 (2016)
8.
Zurück zum Zitat 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: Proceedings of the 8th International Conference on Computer Vision, vol. 2, pp. 416–423 (2001) 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: Proceedings of the 8th International Conference on Computer Vision, vol. 2, pp. 416–423 (2001)
9.
Zurück zum Zitat Meyer, F.: Color image segmentation. In: 1992 International Conference on Image Processing and its Applications, pp. 303–306 (1992) Meyer, F.: Color image segmentation. In: 1992 International Conference on Image Processing and its Applications, pp. 303–306 (1992)
10.
Zurück zum Zitat Nguyen, H.T., Ji, Q.: Improved watershed segmentation using water diffusion and local shape priors. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), vol. 1, pp. 985–992 (2006) Nguyen, H.T., Ji, Q.: Improved watershed segmentation using water diffusion and local shape priors. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), vol. 1, pp. 985–992 (2006)
11.
Zurück zum Zitat Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)CrossRef Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)CrossRef
12.
Zurück zum Zitat Shen, J., Du, Y., Wang, W., Li, X.: Lazy random walks for superpixel segmentation. IEEE Trans. Image Process. 23(4), 1451–1462 (2014)MathSciNetCrossRef Shen, J., Du, Y., Wang, W., Li, X.: Lazy random walks for superpixel segmentation. IEEE Trans. Image Process. 23(4), 1451–1462 (2014)MathSciNetCrossRef
13.
Zurück zum Zitat Sinop, A.K., Grady, L.: A seeded image segmentation framework unifying graph cuts and random walker which yields a new algorithm. In: 2007 IEEE 11th International Conference on Computer Vision, pp. 1–8 (2007) Sinop, A.K., Grady, L.: A seeded image segmentation framework unifying graph cuts and random walker which yields a new algorithm. In: 2007 IEEE 11th International Conference on Computer Vision, pp. 1–8 (2007)
14.
Zurück zum Zitat Zhang, J., Zheng, J., Cai, J.: A diffusion approach to seeded image segmentation. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2125–2132 (2010) Zhang, J., Zheng, J., Cai, J.: A diffusion approach to seeded image segmentation. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2125–2132 (2010)
Metadaten
Titel
Image Segmentation Based on Solving the Flow in the Mesh with the Connections of Limited Capacities
verfasst von
Michael Holuša
Andrey Sukhanov
Eduard Sojka
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-59876-5_19

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