Restoration and reconstruction of grain boundary in metallographical image

JIANG Ming-xing; CHEN Guo-hua

doi:10.3788/OPE.20111910.2541

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Restoration and reconstruction of grain boundary in metallographical image

Article | 更新时间：2020-08-12

- Restoration and reconstruction of grain boundary in metallographical image
- Optics and Precision Engineering Vol. 19, Issue 10, Pages: 2541-2549(2011)
- 作者机构：
  
  1. 华南理工大学机械与汽车工程学院, 广东广州 510640
  2. 华南农业大学理学院, 广东广州 510642
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111910.2541
  CLC： TP391.4
- Received：15 February 2011，
  
  Revised：18 March 2011，
  
  Published Online：27 October 2011，
  
  Published：25 October 2011
- 稿件说明：
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蒋明星, 陈国华. 金相图像的晶界恢复与重建[J]. 光学精密工程, 2011,19(10): 2541-2549

JIANG Ming-xing, CHEN Guo-hua . Restoration and reconstruction of grain boundary in metallographical image[J]. Editorial Office of Optics and Precision Engineering, 2011,19(10): 2541-2549
蒋明星, 陈国华. 金相图像的晶界恢复与重建[J]. 光学精密工程, 2011,19(10): 2541-2549 DOI： 10.3788/OPE.20111910.2541.

JIANG Ming-xing, CHEN Guo-hua . Restoration and reconstruction of grain boundary in metallographical image[J]. Editorial Office of Optics and Precision Engineering, 2011,19(10): 2541-2549 DOI： 10.3788/OPE.20111910.2541.

摘要

针对定量金相分析中金相图像的晶界恢复与重建以及数学形态学在图像处理中的特殊作用

从理论上证明了传统膨胀运算对图像灰度连续性的影响及影响程度与结构元素尺寸的关系

并对传统的膨胀运算的定义做了改进

据此提出了多尺度测地膨胀算法并以此恢复和重建金相图像的晶界。首先依据改进的膨胀运算对金相图像进行预处理;然后用多尺度迭代腐蚀和多尺度测地膨胀方法得到晶粒的种子;最后用条件粗化方法对晶粒的种子进行区域生长、产生晶界线。实验结果表明

与传统的重复测地膨胀方法以及基于微分运算的图像分割等方法相比

本方法不仅可快速恢复与重建晶界线

而且获取的晶界线更加清晰准确、连续光滑。

Abstract

According to the restoration and reconstruction of the grain boundaries in a metallographical image and the important role of mathematical morphology in image processing

the influences of traditional dilation of mathematical morphology on the gray-scale continuity of an image was demonstrated theoretically

and the relationship between the degree of influence and the sizes of structural elements was discussed. Then

an improved definition for the traditional dilation was proposed. A multi-scale geodesic dilation algorithm was presented to restore and reconstruct the grain boundaries based on the improved definition of dilation. First

the metallographical image was preprocessed based on the improved definition of dilation. Second

the seeds of the grains in the metallographical image were gotten by the methods of multi-scale iterative erosion and geodesic dilation. Finally

the grain boundaries in the metallographical image were obtained by the algorithm of conditioned dilation. Experimental results show that the proposed algorithm is not only faster than the traditional methods of geodesic dilation in the restoration and reconstruction of the grain boundary

but also can obtain the grain boundaries with more clearness

accuracy

continuity and smoothness.

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references

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