3D Images of Materials Structures: Processing and Analysis
Taking and analyzing images of materials' microstructures is essential for quality control, choice and design of all kind of products. Today, the standard method still is to analyze 2D microscopy images. But, insight into the 3D geometry of the microstructure of materials and measuring its characteristics become more and more prerequisites in order to choose and design advanced materials according to desired product properties.
This first book on processing and analysis of 3D images of materials structures describes how to develop and apply efficient and versatile tools for geometric analysis and contains a detailed description of the basics of 3d image analysis.
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3D image adjacency systems algorithm analysis B(Rn balls binary image Boolean models characteristics compact computed consider convex sets convolution corresponding covariance function covS defined denote dilation discrete distance transform distribution edge equation estimated Euclidean distance Euler number Example fibre filter filter mask follows foreground pixels formula Fourier transform function f Gauss geometry given grey value grey-value homogeneous lattice image data image processing indicator function integral isotropic label Laguerre tessellation lattice Ln lattice points linear macroscopically homogeneous random mask mean curvature mean width measure methods microstructure Minkowski addition Minkowski sum n-dimensional obtained ofthe packing pair parameter particles pixel pixel configurations pixel spacing pore random closed set random point field reconstruction sample section lattices segmentation simulation sinter smoothing stochastic structuring element struts surface area tessellation theorem threshold tion unit cell vector visualization Volume rendering Voronoļ window