Special Section on Quality Control by Artificial Vision

Quantification of overlapping polygonal-shaped particles based on a new segmentation method of in situ images during crystallization

[+] Author Affiliations
Ola Suleiman Ahmad, Johan Debayle, Nesrine Gherras, Benoît Presles, Jean-Charles Pinoli

École Nationale Supérieure des Mines de Saint-Etienne, LPMG, UMR CNRS 5148, 158 cours Fauriel, 42023 Saint-Etienne Cedex 2, France

Gilles Févotte

École Nationale Supérieure des Mines de Saint-Etienne, LPMG, UMR CNRS 5148, 158 cours Fauriel, 42023 Saint-Etienne Cedex 2, France

Université Lyon 1, Campus de la Doua, 43 Boulevard du 11 Nov. 1918, 69622 Villeurbanne Cedex, France

J. Electron. Imaging. 21(2), 021115 (May 10, 2012). doi:10.1117/1.JEI.21.2.021115
History: Received July 21, 2011; Revised March 6, 2012; Accepted March 9, 2012
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Abstract.  Quantification of the overlapping particles in crystallization processes is very important for the quality control of chemical products or drugs. We present a method of segmentation of polygonal-shaped (i.e., rectangles, regular/irregular prisms) and overlapping particles from in situ images during a crystallization process for measuring their size distributions. The method is first based on detecting the geometric features of the particles identified by their salient corners. A clustering technique is then applied by grouping three correspondent salient corners belonging to the same particle. The proposed method is applied on particles of ammonium oxalate during batch crystallization in pure water. The particle size distributions are calculated, and a quantitative comparison between the proposed method and a manual sizing is performed. The method showed that it is valid for analyzing the crystal growth, and the results are promising for monitoring the particle size distribution.

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© 2012 SPIE and IS&T

Topics

Particles ; Crystals

Citation

Ola Suleiman Ahmad ; Johan Debayle ; Nesrine Gherras ; Benoît Presles ; Gilles Févotte, et al.
"Quantification of overlapping polygonal-shaped particles based on a new segmentation method of in situ images during crystallization", J. Electron. Imaging. 21(2), 021115 (May 10, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.2.021115


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