Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Concrete and Construction Chemistry, Überlandstrasse, Dübendorf, Switzerland.
J Microsc. 2013 Aug;251(2):188-204. doi: 10.1111/jmi.12061. Epub 2013 Jun 21.
An automated image analysis procedure for the segmentation of anhydrous fly ash from backscattered electron images of hydrated, fly ash blended Portland cement paste is presented. A total of six hundred backscattered electron images per sample are acquired at a magnification of 2000. Characteristic features of fly ash particles concerning grey level, shape and texture were used to segment anhydrous fly ash by a combination of grey level filtering, grey level segmentation and morphological filtering techniques. The thresholds for the grey level segmentation are determined for each sample by semiautomatic histogram analysis of the full image stack of each sample. The analysis of the presented dataset reveals a standard deviation of the reaction degree of fly ash of up to 4.3%. The results agree with a selective dissolution method to quantify the reaction degree of fly ash showing the potential of the presented image analysis procedure.
介绍了一种用于从水合粉煤灰掺 Portland 水泥浆的背散射电子图像中分割无水粉煤灰的自动化图像分析程序。每个样本采集总共 600 张背散射电子图像,放大倍数为 2000。使用粉煤灰颗粒的灰度级、形状和纹理等特征,通过灰度级滤波、灰度级分割和形态滤波技术的组合来分割无水粉煤灰。通过对每个样本的全图像堆栈进行半自动直方图分析,确定每个样本的灰度级分割阈值。对所提出数据集的分析表明,粉煤灰反应度的标准偏差高达 4.3%。结果与定量粉煤灰反应度的选择性溶解方法一致,表明了所提出的图像分析程序的潜力。