Image Analysis: Applications in Materials Engineering
Minimizing theoretical background and mathematical formalism, Image Analysis provides basic principles of image acquisition, enhancement, measurements, and interpretation in a very simple form, using an approach toward applications and properties of available tools. The singular study lists different tasks to do and offers complete solutions to these tasks, based on the author's experience with the procedures described.
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8-connected algorithm analyze applied automatic basic binary image boundary lines Brian Ralph bright carbides chapter closing continuous network contrast crack defined described detected grains Detection of grain difficult dilation distance image ductile easily edge detection effect erosion etching eutectic example ferrite fibers final detection Fourier spectrum Fourier transformation fracture surface fuzzy logic gives grain boundary detection graphite gray levels gray-scale illustrated image analysis image analysis tools image processing inhomogeneity initial image Fig Laplacian leads magnification materials science matrix measurements median filter methods microstructure noise Obviously operations orientation parameters particles pixels polished pores possible problem procedure produce properties quantitative regions remove scratches shade correction shape factor sharpening filters shown in Fig simple simulation skeleton SKIZ solution specimen preparation stereology structuring element suitable technique texture threshold level tion top-hat transformation usually visible watershed detection
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