New grayscale morphological operators on hypergraph

Junping Wang; Gangming Liang; Yahui Zheng; Yao Wu

doi:10.1117/12.2281660

21 July 2017 New grayscale morphological operators on hypergraph

Junping Wang, Gangming Liang, Yahui Zheng, Yao Wu

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042023 (2017) https://doi.org/10.1117/12.2281660
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

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.

Citation Download Citation

Junping Wang, Gangming Liang, Yahui Zheng, and Yao Wu "New grayscale morphological operators on hypergraph", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042023 (21 July 2017); https://doi.org/10.1117/12.2281660

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available