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2020 | OriginalPaper | Buchkapitel

20. Digital Microscopy Image Enhancement Technique for Microstructure Image Analysis of Bottom Ash Particle Polymer Composites

verfasst von : F. A. Hermawati, I. M. Kastiawan, Muhyin

Erschienen in: Advanced Materials

Verlag: Springer International Publishing

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Abstract

Polymer composites are composite materials with matrices of polymers with reinforcements using fibers or particles or both together. This study uses polypropylene polymer composite material with reinforcement of bottom ash particles. In the manufacture of polypropylene-shaped sheet (lamina) polymer composite materials with bottom ash particles, the process of assessing the composite characteristics of the polypropylene matrix such as the level of distribution of bottom ash particles as fillers in the polypropylene matrix through microscopic images is necessary. Analysis of the level of distribution of reinforcement particle is used to avoid the formation of filler particle agglomerates during the dispersion of various types of fillers in polymer resins. Bottom ash particles themselves have an irregular shape that requires particular analysis to distinguish a single particle and an agglomerate particle. Before the analysis step, the most crucial step at the beginning is to carry out the process of improving the quality of the input image, which aims to improve image contrast and eliminate unwanted noise. This chapter proposes an image enhancement method to enhance the quality of the microstructure image of a polymer composite that is analyzed using a digital microscope. The proposed method combines the multiresolution approach and the anisotropic diffusion method. From the experiment, this image enhancement method gives the best performance when it is compared with other techniques in the state of the arts.

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Metadaten
Titel
Digital Microscopy Image Enhancement Technique for Microstructure Image Analysis of Bottom Ash Particle Polymer Composites
verfasst von
F. A. Hermawati
I. M. Kastiawan
Muhyin
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-45120-2_20

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