Shape robustness in style enhanced cross domain semantic segmentation

Zhu, Siyu

doi:10.1016/j.patcog.2022.109143

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Despite the significant progress made by metaheuristic algorithm-enhanced Otsu methods in various application domains, their robustness [ 70 ] and segmentation accuracy remain inadequate when dealing with images containing complex lighting, angles, and texture variations, such as rubber tree tapping scars and latex images. The computational complexity is also relatively high.…”

Section: Introductionmentioning

confidence: 99%

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

Xie,

Wu,

Tang

et al. 2024

PLoS ONE

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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.

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Section: Introductionmentioning

confidence: 99%