An optimization-based approach to extract faceted crystal shapes from stereoscopic images
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Author (Corporation)
Publication date
06.04.2015
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Type
01A - Journal article
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Parent work
Computers & Chemical Engineering
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Volume
75
Issue / Number
Pages / Duration
171-183
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Publisher / Publishing institution
Elsevier
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Abstract
The size and shape of particles crucially influences the characteristics of solid products. Until recently these quantities were evaluated using light microscopy. However, extracting the three-dimensional shape of a faceted crystal from a single image is a formidable computer vision challenge. In this work we combine stereoscopic imaging devices (e.g., commercial stereoscopic microscopes or the stereoscopic flow through cell that continuously draws samples from a crystallizer (Schorsch et al., 2014)) with a model-based approach in which parametric polytopes are used to describe faceted crystals (Hours et al., 2014). In the shape reconstruction algorithm these parametric polytopes are scaled and rotated until their projections closely match the measured stereoscopic images, which is formulated as a nonlinear optimization problem. The proposed approach is assessed using simulated images and experimental data. We also assess in which cases the proposed approach does or does not provide advantages over concepts using generic particle shapes (Schorsch et al., 2012).
Keywords
Crystallization, Particle shape, Particulate processes, Stereoscopic imaging, Faceted crystals, Nonlinear optimization
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0098-1354
1873-4375
1873-4375
Language
English
Created during FHNW affiliation
No
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Publication status
Published
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Peer review of the complete publication
Open access category
Green
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Citation
Schorsch, S., Hours, J.-H., Vetter, T., Mazzotti, M., & Jones, C. N. (2015). An optimization-based approach to extract faceted crystal shapes from stereoscopic images. Computers & Chemical Engineering, 75, 171–183. https://doi.org/10.1016/j.compchemeng.2015.01.016