Abstract
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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