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Advancing image segmentation with DBO-Otsu: Addressing rubber tree diseases through enhanced threshold techniques

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  • Zhenjing Xie
  • Jinran Wu
  • Weirui Tang
  • Yongna Liu

Abstract

Addressing the profound impact of Tapping Panel Dryness (TPD) on yield and quality in the global rubber industry, this study introduces a cutting-edge Otsu threshold segmentation technique, enhanced by Dung Beetle Optimization (DBO-Otsu). This innovative approach optimizes the segmentation threshold combination by accelerating convergence and diversifying search methodologies. Following initial segmentation, TPD severity levels are meticulously assessed using morphological characteristics, enabling precise determination of optimal thresholds for final segmentation. The efficacy of DBO-Otsu is rigorously evaluated against mainstream benchmarks like Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM), and compared with six contemporary swarm intelligence algorithms. The findings reveal that DBO-Otsu substantially surpasses its counterparts in image segmentation quality and processing speed. Further empirical analysis on a dataset comprising TPD cases from level 1 to 5 underscores the algorithm’s practical utility, achieving an impressive 80% accuracy in severity level identification and underscoring its potential for TPD image segmentation and recognition tasks.

Suggested Citation

  • Zhenjing Xie & Jinran Wu & Weirui Tang & Yongna Liu, 2024. "Advancing image segmentation with DBO-Otsu: Addressing rubber tree diseases through enhanced threshold techniques," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-30, March.
    • Handle: RePEc:plo:pone00:0297284
    DOI: 10.1371/journal.pone.0297284
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    References listed on IDEAS

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    1. Xiaofeng Qu & Jiajun Wang & Xiaoling Wang & Yike Hu & Tianwen Tan & Dong Kang, 2023. "Fast detection of dam zone boundary based on Otsu thresholding optimized by enhanced harris hawks optimization," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-17, February.
    2. Sajad Ahmad Rather & Sujit Das, 2023. "Levy Flight and Chaos Theory-Based Gravitational Search Algorithm for Image Segmentation," Mathematics, MDPI, vol. 11(18), pages 1-56, September.
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