PRACTICAL METHOD FOR IMAGE SEGMENTATION USING MULTIFRACTAL DETRENDED FLUCTUATION ANALYSIS COMBINED WITH GRAY–SCOTT MODEL
In this paper, a novel image segmentation method (MF-GS-DFA) using multifractal detrended fluctuation analysis (MF-DFA) combined with the Gray–Scott model is proposed, which is an improvement and extension of MF-DFA. Experimental results show that MF-GS-DFA retains high-precision details in segmenting natural and medical images and effectively extracts the contours and fine structures of target objects, overcoming the noise-sensitive limitations of MF-DFA. In addition, our proposed method also shows strong adaptability and robustness in processing images with complex backgrounds and rich texture features, providing a novel solution for biomedical engineering.
Authors
- Ke Chen (ORCID: https://orcid.org/0009-0007-8832-0189)
- Jian Wang (ORCID: https://orcid.org/0000-0003-2615-0755)
- Y. Wang (ORCID: https://orcid.org/0009-0006-0037-7248)
- Lin Wu (ORCID: https://orcid.org/0000-0003-3595-2207)
- R. Xu (ORCID: https://orcid.org/0000-0003-4674-9482)
- Qin Liu (ORCID: https://orcid.org/0000-0003-0719-148X)
- Yu Wang (ORCID: https://orcid.org/0000-0003-0707-8727)
- R. Peng
Institutions
- Nanjing University of Information Science and Technology (CN)
Publication Details
- Journal
- Fractals
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1142/s0218348x25500793
- Primary Topic
- Complex Systems and Time Series Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00