Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/106515
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dc.titleA pellet sphericity measure system based on dual active contour models
dc.contributor.authorShi, D.-M.
dc.contributor.authorHeng, P.W.S.
dc.contributor.authorChen, F.
dc.date.accessioned2014-10-29T02:01:08Z
dc.date.available2014-10-29T02:01:08Z
dc.date.issued2003
dc.identifier.citationShi, D.-M.,Heng, P.W.S.,Chen, F. (2003). A pellet sphericity measure system based on dual active contour models. International Conference on Machine Learning and Cybernetics 5 : 2781-2784. ScholarBank@NUS Repository.
dc.identifier.isbn0780378652
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/106515
dc.description.abstractThe spherical granules play very important role in pharmaceutical manufacturing, since spheroids are ideal for coating as their shape allows for the application of a uniform layer of coating material. There are many factors affecting the pellet sphericity in shperonization process, such as the starting materials, spheronization speed, residence time, etc. A satisfactory sphericity measure can indicate how to adjust the starting materials and the operating variables. In this paper, edge detection is employed to obtain a pellet image boundary robustly and then calculate the pellet sphericity. Active contour models, also termed as snakes by the nature of their evolution are a sophisticated approach to contour extraction. Conventional snakes suffer difficulty in appropriate choice of an initial contour and values of parameters. The dual active contour models can relieve this problem by combining with a local shape model to improve the parameterization. This methodology has been applied to our sphericity measure system.
dc.sourceScopus
dc.subjectDual active contour model
dc.subjectImage processing
dc.subjectPharmaceutical manufacturing
dc.subjectSphericity
dc.typeConference Paper
dc.contributor.departmentPHARMACY
dc.description.sourcetitleInternational Conference on Machine Learning and Cybernetics
dc.description.volume5
dc.description.page2781-2784
dc.identifier.isiutNOT_IN_WOS
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