Progress of Quantitative Estimating Techniques for Metallographic Grain Size

SUN Chao-ming; MENG Yu-tang; YANG Gui-zhu

PHYSICAL TESTING AND CHEMICAL ANALYSIS PART A:PHYSICAL TESTING > 2012 > 48(12): 814-817.

SUN Chao-ming, MENG Yu-tang, YANG Gui-zhu. Progress of Quantitative Estimating Techniques for Metallographic Grain Size[J]. PHYSICAL TESTING AND CHEMICAL ANALYSIS PART A:PHYSICAL TESTING, 2012, 48(12): 814-817.

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Progress of Quantitative Estimating Techniques for Metallographic Grain Size

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Received Date: June 27, 2012

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The key techniques of quantitative estimating for metallographic grain size were discussed, the development situations of estimating for grain size at home and abroad were introduced subsequently, and the future of estimating for grain size was clarified in the end. For complex metallographic images, problems of accurate extraction and reconstruction of grain boundaries would be solved in the near future, and quantitative estimating for grain size by software automatically or with less human intervention is expected to realize correspondingly to meet with the actual needs in factory.
- metallographic grain size,
- quantitative estimating,
- grain size estimating software,
- automation

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[1]	黄丽华, 王家平. 金相图像分析仪的现状及发展前景探讨[J]. 光学仪器, 2003, 25(6): 50-53.
[2]	GOUTSIAS J, VINCENT L, BLOOMBERG D S. Mathematical morphology and its applications to image and signal processing[M]. New York:Kluwer Academic Publishers,2000:3-70.
[3]	BEUCHER S. Numerical residues[J]. Image and Vision Computing, 2007, 25: 405-415.
[4]	MAHADEVAN S,CASASENT D. Automated image processing for grain boundary analysis[J]. Ultramicroscopy,2003,96:153-162.
[5]	SHIH F Y. Image processing and mathematical morphology:Fundamentals and applications[M]. Boca Raton:CRC Press,2009:354-357.
[6]	LATALCA Z,WOJNAR L. Computer-aided versus manual grain size assessment in a single phase material[J]. Materials Characterization, 2001, 46: 227-233.
[7]	LAHAYE C T W. Daily routine quantitative assessment of microstructure of steel by image analysis[J]. Materials Characterization,1996, 36: 191-202.
[8]	HEILBORONNER R. Automatic grain boundary detection and grain size analysis using polarization micrographs or orientation images[J]. Journal of Structural Geology,2000, 22:969-981.
[9]	MALY M,HRACH R,NOVOTNY D. Intelligent reconstruction of grain structures in images of 2D cuts of crystalline materials[J]. Applied Surface Science, 2004, 235: 86-90.
[10]	孙秋冬, 颜文英, 戴虹,等. 金相图像处理与分析[J]. 计算机应用与软件, 2006, 23(8):100-102.
[11]	王建萍, 王家平, 许建广. 数字图像处理在定量金相分析中的应用[J]. 材料导报, 2003, 17(1):63-65.
[12]	李新城, 王有鹏, 朱伟兴,等. 基于形态学的金相组织图像晶界复原方法[J]. 计算机工程与设计, 2008, 29(14): 3807-3809.
[13]	罗以宁, 李毅, 杨凯. 金相图像分析中一种改进的断点连接方法[J]. 四川大学学报(自然科学版), 2002, 39(6): 1027-1031.
[14]	何小海,滕奇志,张轶琼. 基于模糊边缘检测的复杂晶界的重建[J]. 理化检验-物理分册,2005, 41(11): 566-572.

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