Automatic Binary Data Classification Using a Modified Allen-Cahn Equation

Sangkwon Kim, Junseok Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In this paper, we propose an automatic binary data classification method using a modified Allen-Cahn (AC) equation. The modified AC equation was originally developed for image segmentation. The equation consists of the AC equation with a fidelity term which enforces the solution to be the given data. In the proposed method, we start from a coarse grid and refine the grid until the accuracy of the data classification reaches a given tolerance. Therefore, we can avoid a laborious trial and error procedure. For a numerical method for the modified AC equation, we use a recently developed explicit hybrid scheme. We perform several 2D and 3D computational tests to demonstrate the performance of the proposed method. The computational results confirm that the proposed algorithm is automatic.

Original languageEnglish
Article number2150013
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume35
Issue number4
DOIs
Publication statusPublished - 2021 Mar 30

Bibliographical note

Funding Information:
The corresponding author (J. S. Kim) was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1A2C1003053). The authors thank the editor and the reviewers for their constructive and helpful comments on the revision of this paper.

Publisher Copyright:
© 2021 World Scientific Publishing Company.

Keywords

  • Binary data classification
  • modified Allen-Cahn equation
  • operator splitting method

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Automatic Binary Data Classification Using a Modified Allen-Cahn Equation'. Together they form a unique fingerprint.

Cite this