IMAGE ANALYTICAL DETERMINATION OF THE SPHERULITE GROWTH IN POLYPROPYLENE COMPOSITES
DOI:
https://doi.org/10.5566/ias.1895Keywords:
Hough transform, homography estimationAbstract
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.
References
De Santis F, Scermino R, Pantani R, Titomanlio G (2014). Spherulitic nucleation and growth rates in a sheared polypropylene melt. AIP Conference Proceedings 2014 1593(1):294-7
Hartley R, Zisserman A (2003). Multiple View Geometry in Computer Vision (2nd ed.). Cambridge University Press, New York, NY, USA.
Hernández-Sánchez, F, Carrillo-Escalante, H (2009). A Study of the Kinetics of Polylactic Acid Crystallization by Image Processing. MRS Proceedings, 1242. doi:10.1557/PROC-1242-S4-P102
Margolin R, Tal A, Zelnik-Manor L (2013). What Makes a Patch Distinct? In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '13). 2013, IEEE, Washington DC, USA, 1139-46. doi: http://dx.doi.org/10.1109/CVPR.2013.151
Mosaliganti K, Gelas A, Cowgill P, Megason S (2009). An Optimized N-Dimensional Hough Filter for Detecting Spherical Image Objects. The Insight Journal 2009, http://hdl.handle.net/10380/3129
Nomai J, Suksut B, Schlarb AK (2015). Crystallization Behavior of Poly(lactic acid)/Titanium Dioxide Nanocomposites, KMUTNB Int J Appl Sci Technol 8(4):251–8, dx.doi.org/10.14416/j.ijast.2015.10.003
Plummer CJG, Kausch HH (1995). Real-time image analysis and numerical simulation of isothermal spherulite nucleation and growth in polyoxymethylene. Colloid Polym Sci 273(8):719-32. doi:10.1007/BF00658750
Stoyan S, Kendall WS, Mecke J (1995). Stochastic Geometry and its Applications (2nd ed.). John Wiley & Sons, Chichester—New York—Brisbane—Toronto—Singapore.
Thanomchat S, Srikulkit K, Suksut B, Schlarb AK (2014). Morphology and crystallization of polypropylene/microfibrillated cellulose composites. KMUTNB Int J Appl Sci Technol 7(4):23–34, dx.doi.org/10.14416/j.ijast.2014.09.002
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