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多级值图像细分用于树切割使用改进的Otsu的方法和蛇优化器.

Shenghan Li1, Linlin Ye1

  • 1Hainan University, Haikou 570228, China.

Mathematical biosciences and engineering : MBE
|June 16, 2023
PubMed
概括
此摘要是机器生成的。

在树中早期诊断板干燥 (TPD) 非常重要. 一种新的SO-Otsu图像细分方法提高了TPD诊断的效率和准确性,优于现有的技术.

关键词:
奥图的方法是Otsu的方法图像细分 图像细分蛇优化器的蛇优化器触摸板的干燥性 触摸板的干燥性

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科学领域:

  • 农业科学 农业科学
  • 计算机视觉 计算机视觉
  • 图像处理 图像处理

背景情况:

  • 挖掘板干燥 (TPD) 显著减少了天然的生产.
  • 早期诊断TPD对于有效管理树至关重要.
  • 图像细分技术可以帮助早期检测和诊断TPD.

研究的目的:

  • 开发一种高效的图像细分方法,用于在树中诊断TPD.
  • 为了增强Otsu对TPD图像多层次值的方法.
  • 与其他优化算法对比,评估建议的SO-Otsu方法.

主要方法:

  • 研究了TPD图像属性,并改进了Otsu的方法.
  • 将蛇优化器与改进的Otsu的方法相结合,创建了SO-Otsu.
  • 将SO-Otsu与其他六种图像分割算法进行比较.

主要成果:

  • 与竞争方法相比,SO-Otsu表现出优越的性能.
  • 提出的方法在运行时间,细节效果和准确度方面表现出色.
  • SO-Otsu被证明是TPD图像的高效图像细分技术.

结论:

  • SO-Otsu是一种有效和高效的方法来细分TPD图像.
  • SO-Otsu方法为TPD诊断提供了更高的准确性和速度.
  • 这种方法可以提高在种植园中提前检测和管理挖掘板干燥的效果.