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Automatic Fiber Thickness Measurement in Scanning Electron Microscopy Images Validated Using Synthetic Data
Author(s) -
Easwaran Prakash,
Lehmann Martin J.,
Wirjadi Oliver,
Prill Torben,
Didas Stephan,
Redenbach Claudia
Publication year - 2016
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201500342
Subject(s) - filter (signal processing) , fiber , scanning electron microscope , context (archaeology) , computer science , process (computing) , materials science , computer vision , artificial intelligence , optics , biomedical engineering , engineering , composite material , physics , paleontology , biology , operating system
Among the various properties of fibrous filter media, fiber thickness is one of the important characteristics which should be considered in design and quality assurance of filter media. Automatic analysis of images from scanning electron microscopy (SEM) is a suitable tool in that context. Yet, the accuracy of such image analysis tools cannot be judged based on images of real filter media since their true fiber thickness can never be known accurately. A solution is to employ synthetically generated models for evaluation. To this end, a 3D fiber model is extended to incorporate fiber bundles, which are common in fibrous filter media. The resulting novel stochastic 3D fiber model can generate geometries with good visual resemblance of real filter media. By combining this model with simulation of the SEM imaging process, quantitative evaluation of the fiber thickness measurements becomes feasible.