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Proceedings Paper

New grayscale morphological operators on hypergraph
Author(s): Junping Wang; Gangming Liang; Yahui Zheng; Yao Wu
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Paper Abstract

New grayscale morphological operators on hypergraph are proposed to avoid the loss of details caused by fixed structure element effectively. Hypergraph, the most general structure in discrete mathematics, is also a subset of a finite set. Being a structured representation of information, the ordinary image can be transformed into a hypergraph model, which can integrate hypergraph theory with mathematical morphology theory. Because hypergraphs have good performance in structuring information, first of all, this paper designs a reasonable method of turning grayscale images into hypergraph space. Then based on hypergraph theory, new grayscale morphological operators on hypergraph are defined. Experiments show that using the new operators can avoid the loss of image detail information, and improve the precision of image processing.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042023 (21 July 2017); doi: 10.1117/12.2281660
Show Author Affiliations
Junping Wang, Xidian Univ. (China)
Gangming Liang, Xidian Univ. (China)
Yahui Zheng, Xidian Univ. (China)
Yao Wu, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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