Recognizing overlapped particles during a crystallization process from in situ video images for measuring their size distributions

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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Journal of Electronic Imaging, SPIE and IS&T, 2012, 21 (2), pp.0211115. 〈10.1117/1.JEI.21.2.021115〉
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Ola Ahmad, Johan Debayle, Nesrine Gherras, Benoît Presles, Gilles Févotte, et al.. Recognizing overlapped particles during a crystallization process from in situ video images for measuring their size distributions. Journal of Electronic Imaging, SPIE and IS&T, 2012, 21 (2), pp.0211115. 〈10.1117/1.JEI.21.2.021115〉. 〈hal-00733252〉

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