聚丙烯复合材料中球晶生长的图像分析测定

IF 0.8 4区 计算机科学 Q4 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Image Analysis & Stereology Pub Date : 2018-07-09 DOI:10.5566/IAS.1895
A. Moghiseh, K. Schladitz, A. Schlarb, B. Suksut
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引用次数: 0

摘要

测量半结晶热塑性塑料中球晶的生长有助于控制和优化这些材料的工业制造过程。生长可以在交叉偏振图像中观察到,在几个时间步骤中拍摄。然而,球粒的直径在每一步都是人工测量的。本文介绍了两种用自动图像分析测量代替这种繁琐、耗时的方法。第一种方法通过在每个时间框架中找到显著的5x5像素块来分割球粒。将所有时间框架的信息组合成3D图像,通过3D切割的最大流图生成球粒。然后用单应性测量来测量生长。第二种方法更接近于手工方法。基于霍夫变换,球晶由其圆形轮廓来识别。然后通过比较最小移动圆的半径来测量增长。根据合成图像数据以及与人工测量的生长速率进行比较,讨论了这些方法的优缺点。
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IMAGE ANALYTICAL DETERMINATION OF THE SPHERULITE GROWTH IN POLYPROPYLENE COMPOSITES
Measuring the growth of spherulites in semi-crystalline thermoplastics helps to control and optimize industrial manufacturing processes of these materials. The growth can be observed in cross polarized images, taken at several time steps. The diameters of the spherulites are however measured manually in each step. Here, two approaches for replacing this tedious and time consuming method by automatic image analytic measurements are introduced. The first approach segments spherulites by finding salient 5x5 pixel patches in each time frame. Combining the information from all time frames into a 3D image yields the spherulites by a maximal flow graph cut in 3D. The growth is then measured by homography measurement. The second approach is closer to the manual method. Based on the Hough transform, spherulites are identified by their circular outline. The growth is then measured by comparing the radia of the least moving circles. The pros and cons of these methods are discussed based on synthetic image data as well as by comparison with manually measured growth rates. 
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来源期刊
Image Analysis & Stereology
Image Analysis & Stereology MATERIALS SCIENCE, MULTIDISCIPLINARY-MATHEMATICS, APPLIED
CiteScore
2.00
自引率
0.00%
发文量
7
审稿时长
>12 weeks
期刊介绍: Image Analysis and Stereology is the official journal of the International Society for Stereology & Image Analysis. It promotes the exchange of scientific, technical, organizational and other information on the quantitative analysis of data having a geometrical structure, including stereology, differential geometry, image analysis, image processing, mathematical morphology, stochastic geometry, statistics, pattern recognition, and related topics. The fields of application are not restricted and range from biomedicine, materials sciences and physics to geology and geography.
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