| 橡胶复合材料中炭黑微观结构图像的拟合算法 |
| Fitting Algorithm of Microstructure Image of Carbon Black Reinforced Rubber Composites |
| 投稿时间：2022-04-16 修订日期：2022-04-16 |
| DOI：10.12136/j.issn.1000-890X.2023.01.0068 |
| 中文关键词: 橡胶复合材料 炭黑补强 炭黑聚集体 微观结构 图像处理 拟合算法 轮廓骨架算法 峰值信噪比 结构相似度 |
| 英文关键词: rubber composite carbon black reinforcing carbon black aggregate microstructure image processing fitting algorithm contour skeleton algorithm PSNR SSIM |
| 基金项目:国家重点研发计划项目(2018YFB1502501) |
|
| 摘要点击次数: 804 |
| 全文下载次数: 522 |
| 中文摘要: |
| 将炭黑聚集体视为由多个圆形原生粒子构成，对橡胶复合材料中炭黑聚集体形态进行图像拟合分析。基于炭黑补强橡胶复合材料的微观结构图像，在采用图像分割和阈值迭代等方法处理图像背景缺陷的基础上，研究了轮廓骨架算法、最大内切圆算法和K-means聚类算法3种拟合算法处理炭黑聚集体图像，并用峰值信噪比和结构相似度2个指标对图像拟合效果进行评价。结果表明，轮廓骨架算法拟合炭黑聚集体形态效果最优，更适用于炭黑补强橡胶复合材料微观结构重构时对炭黑聚集体形态的描述。 |
| 英文摘要: |
| Carbon black aggregates were considered to be composed of multiple circular primary
particles，and the morphology of carbon black aggregates in rubber composites was analyzed by image fitting.
Based on the microstructure image of carbon black reinforced rubber composites，three fitting algorithms，
contour skeleton algorithm，maximum inscribed circle algorithm and K-means clustering algorithm to deal
with carbon black aggregate morphology were studied based on using image segmentation and threshold
iteration and other methods to handle image background defects. The image fitting effects were evaluated
by two indicators of peak signal-to-noise ratio（PSNR）and structural similarity（SSIM）. The results showed
that the contour skeleton algorithm had the best effect in fitting the morphology of carbon black aggregates，
and it was more suitable for describing the morphology of carbon black aggregates in the microstructure
reconstruction of carbon black reinforced rubber composites. |
|
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
