Average Grain Size Determination Using Mathematical Morphology and Texture Analysis
Average Grain Size Determination Using Mathematical Morphology and Texture Analysis
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使用数学形态学和织构分析确定平均晶粒尺寸
DOI：
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
O. Silvén
中科院分区：
文献类型：
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作者：
Hannu Rautio;O. Silvén
许多工业过程需要有关材料粒度的信息。在这项工作中，我们检查了轧制铬精矿以确定平均晶粒尺寸。测试材料从下午 37 点到下午 500 点被筛分为 15 个部分。分析方法可分为三个部分：预处理、特征提取和分类。采用数学形态学作为预处理方法，以灰度腐蚀和开运算作为运算。特征提取是通过一阶和二阶统计来实现的。最后，使用k-NN和最小距离分类器使用留出法进行分类。我们得出的结论是，数学形态学和纹理分析可用于确定材料的平均晶粒尺寸。它计算简单且快速，但对于较小的颗粒类别不太准确。这是由于成像误差和噪声造成的，而且还因为晶粒尺寸与结构元素尺寸的比率必须足够大。开运算和腐蚀运算都可以使用。侵蚀比打开执行快两倍。另外，预处理操作的数量可以减少到例如三个，而分类结果不会有显着的变化。
Many industrial processes need information about material grain size. In this work we examined rolled chrome concentrate to determine the average grain size. Test material was sieved into 15 fractions, from 37 pm to 500 pm. The analysis method can be divided in three sections: preprocessing, feature extraction and classification. Mathematical morphology was used as preprocessing method, with gray-scale erosion and opening as operations. Feature extraction was implemented with first and second-order statistics. Finally, classification was performed with k-NN and minimum distance classifiers using leave-out method. We conclude that mathematical morphology with texture analysis can be used to determine average grain size of material. It is computationally easy and fast although less accurate to smaller grain classes. This is due to imaging errors and noise but also the fact that the ratio grain size versus size of structuring element must be large enough. Both opening and erosion operations can be used. Erosion is two times faster than opening to perform. Also the number of preprocessing operations can be, for example, reduced to three without the classification result will have a remarkable change.