An image-based approach for quantitative assessment of uniformity in particle distribution of noise reduction material,Microscopy Research and Technique

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An image-based approach for quantitative assessment of uniformity in particle distribution of noise reduction material
Microscopy Research and Technique ( IF 2.0 ) Pub Date : 2021-03-09 , DOI: 10.1002/jemt.23748
Hua Tan ₁ , Zhang-Can Huang ₁ , Si-Rong Zhu ₁ , Lang He ₁ , Xi Fang ₁

Affiliation

Under the background of noise pollution caused by railway development, noise reduction material is worthy of in-depth study. A uniform distribution of particles in the material has an important influence on sound absorption property. In this article, the relevant image processing technology is applied to get structure information to quantify the uniformity. The main contributions of this study are: (a) In the preprocessing stage, SEM cross-sectional image of material is processed by mean filter and histogram equalization. Therefore, the grayscale and the contrast between target and background are enhanced, and a low-quality image is transformed into a high-quality one. (b) In the locating stage, local details of the image are considered to discriminate each particle from the whole image. When a global threshold is combined with the local iteration threshold, an improved Otsu algorithm is designed to binarize the image. Through morphology transforming, area filtering, and hole filling, the connected domain of target can be found and particles are located. (c) In the assessing stage, area index, number index and local distance index are established for assessing the uniformity of pore distribution. The experimental results indicate that statistical analysis is consistent with human visual observation. The smaller the porosity is, the better the uniformity is. Compared with some important methods, the effectiveness and efficiency of the proposed approach could be illustrated.

中文翻译：

一种基于图像的降噪材料颗粒分布均匀性定量评估方法

在铁路发展造成噪声污染的背景下，降噪材料值得深入研究。材料中颗粒的均匀分布对吸声性能有重要影响。本文应用相关图像处理技术获取结构信息，对均匀性进行量化。本研究的主要贡献是： (a) 在预处理阶段，材料的 SEM 横截面图像经过均值滤波和直方图均衡处理。因此，增强了目标与背景之间的灰度和对比度，将低质量的图像转换为高质量的图像。(b) 在定位阶段，考虑图像的局部细节以从整个图像中区分每个粒子。当全局阈值与局部迭代阈值相结合时，设计了一种改进的Otsu算法对图像进行二值化。通过形态变换、区域过滤和孔洞填充，可以找到目标的连通域并定位粒子。(c) 在评价阶段，建立面积指数、数量指数和局部距离指数来评价孔隙分布的均匀性。实验结果表明统计分析与人类目视观察一致。孔隙率越小，均匀性越好。与一些重要的方法进行比较，可以说明所提出方法的有效性和效率。可以找到目标的连通域并定位粒子。(c) 在评价阶段，建立面积指数、数量指数和局部距离指数来评价孔隙分布的均匀性。实验结果表明统计分析与人类目视观察一致。孔隙率越小，均匀性越好。与一些重要的方法进行比较，可以说明所提出方法的有效性和效率。可以找到目标的连通域并定位粒子。(c) 在评价阶段，建立面积指数、数量指数和局部距离指数来评价孔隙分布的均匀性。实验结果表明统计分析与人类目视观察一致。孔隙率越小，均匀性越好。与一些重要的方法进行比较，可以说明所提出方法的有效性和效率。

更新日期：2021-03-09

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