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一种基于行列灰度分割的多层多通珠截面形态提取方法.

Ting Lei1,2, Shixiang Gong1,2, Chaoqun Wu1,2

  • 1School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430070, China.

Materials (Basel, Switzerland)
|October 16, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种用于提取珠截面形态的自动化方法,提高接质量分析的一致性和效率. 新技术准确地识别了关键特征,有助于更好地评估接.

关键词:
特性提取方法的方法.图像识别 图像识别 图像识别多层多通的多层多通的接珠子形态学 接珠子形态学

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科学领域:

  • 材料科学与工程 材料科学与工程
  • 非破坏性测试是指非破坏性测试.
  • 图像处理 图像处理

背景情况:

  • 接珠的截面形态对于评估接质量至关重要.
  • 手动提取方法是不一致和低效的.
  • 为了可靠的质量控制,需要自动提取.

研究的目的:

  • 开发一种用于提取多层,多通珠横截面形态的自动化方法.
  • 提高接质量分析的一致性和效率.
  • 为详细分析和改进接质量评估提供基础.

主要方法:

  • 珠截面图像的图像预处理.
  • 基于平均灰色值的行列灰度分段.
  • 使用二元化值 (ESI) 提取接轮.
  • 图像融合和形态处理用于特征提取.
  • 计算接特征参数,如周长和面积.

主要成果:

  • 周长和面积的相对误差在10%以内.
  • 最大接接的宽度和高度差异接近真实值.
  • 高图像质量评估,平均SSIM>0.9和平均PSNR>60.
  • 对于多层,多通接的一般轮特征的可行提取.

结论:

  • 拟议的自动化方法有效地提取珠横截面形态.
  • 该技术比手工方法提供了更高的准确性和效率.
  • 这为加强接质量评估和控制提供了基础.