Fast and Efficient Numerical Finite Difference Method for Multiphase Image Segmentation. (20th November 2021)
- Record Type:
- Journal Article
- Title:
- Fast and Efficient Numerical Finite Difference Method for Multiphase Image Segmentation. (20th November 2021)
- Main Title:
- Fast and Efficient Numerical Finite Difference Method for Multiphase Image Segmentation
- Authors:
- Li, Yibao
Yoon, Sungha
Wang, Jian
Park, Jintae
Kim, Sangkwon
Lee, Chaeyoung
Kim, Hyundong
Kim, Junseok - Other Names:
- Gálvez Akemi Academic Editor.
- Abstract:
- Abstract : We present a simple numerical solution algorithm for a gradient flow for the Modica–Mortola functional and numerically investigate its dynamics. The proposed numerical algorithm involves both the operator splitting and the explicit Euler methods. A time step formula is derived from the stability analysis, and the goodness of fit of transition width is tested. We perform various numerical experiments to investigate the property of the gradient flow equation, to verify the characteristics of our method in the image segmentation application, and to analyze the effect of parameters. In particular, we propose an initialization process based on target objects. Furthermore, we conduct comparison tests in order to check the performance of our proposed method.
- Is Part Of:
- Mathematical problems in engineering. Volume 2021(2021)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11-20
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2021/2414209 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 20099.xml