Huo, Y, Liu, T, Liu, H et al. (2 more authors) (2016) In-situ crystal morphology identification using imaging analysis with application to the L-glutamic acid crystallization. Chemical Engineering Science, 148. pp. 126-139. ISSN 0009-2509
Abstract
A synthetic image analysis strategy is proposed for in-situ crystal size measurement and shape identification for monitoring crystallization processes, based on using a real-time imaging system. The proposed method consists of image processing, feature analysis, particle sieving, crystal size measurement, and crystal shape identification. Fundamental image features of crystals are selected for efficient classification. In particular, a novel shape feature, referred to as inner distance descriptor, is introduced to quantitatively describe different crystal shapes, which is relatively independent of the crystal size and its geometric direction in an image captured for analysis. Moreover, a pixel equivalent calibration method based on subpixel edge detection and circle fitting is proposed to measure crystal sizes from the captured images. In addition, a kernel function based method is given to deal with nonlinear correlations between multiple features of crystals, facilitating computation efficiency for real-time shape identification. Case study and experimental results from the cooling crystallization of l-glutamic acid demonstrate that the proposed image analysis method can be effectively used for in-situ crystal size measurement and shape identification with good accuracy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, Elsevier. This is an author produced version of a paper published in Chemical Engineering Science. Uploaded in accordance with the publisher's self-archiving policy |
Keywords: | Crystal morphology; Shape identification; Imaging analysis; Feature analysis; Inner distance descriptor |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) > Institute for Particle Science and Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 May 2016 12:31 |
Last Modified: | 13 Apr 2017 19:54 |
Published Version: | http://dx.doi.org/10.1016/j.ces.2016.03.039 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ces.2016.03.039 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99208 |