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Interactive image segmentation via superpixel pairs probabilistic diffusion
Author(s): Yu Xia; Tao Wang; Zexuan Ji
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Paper Abstract

This paper introduces a new interactive image segmentation approach based on global pairwise relationship. Many conventional interactive image segmentation methods only consider local relationship of neighboring pixels or unary probability of pixels, which results in the sensitivity to seeds. To overcome this drawback, we utilizes the pixel-pairwise relationship to obtain the global pairwise relationship of pixels. The constructed global binary probability is used to estimate the labels of pixels. In order to improve the computational efficiency, we further replace pixels with superpixels and use the binary global relationship of superpixels for image segmentation. Our method makes full use of global binary information and has stronger robustness to limited seeds information. The superior performances of our method are demonstrated in the experiments on the Berkeley segmentation dataset and Microsoft GrabCut database.

Paper Details

Date Published: 3 January 2020
PDF: 9 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113731F (3 January 2020); doi: 10.1117/12.2557592
Show Author Affiliations
Yu Xia, Nanjing Univ. of Science and Technology (China)
Tao Wang, Nanjing Univ. of Science and Technology (China)
Zexuan Ji, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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