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Sugar crystal size characterization using digital image processing.

dc.contributor.advisorAlport, Michael J.
dc.contributor.advisorMalinga, Sandile B.
dc.contributor.authorArgaw, Getachew Abebe.
dc.descriptionThesis (PhD)-University of KwaZulu-Natal, Durban, 2007.en_US
dc.description.abstractThe measurement of the crystal size distribution is a key prerequisite in optimising the growth of sugar crystals in crystalisation pans or for quality control of the final product. Traditionally, crystal size measurements are carried out by inspection or using mechanical sieves. Apart from being time consuming, these techniques can only provide limited quantitative information. For this reason, a more quantitative automatic system is required. In our project, software routines for the automated measurement of crystal size using classical image analysis techniques were developed. A digital imaging technique involves automatically analyzing a captured image of a representative sample of ~ 100 crystals for the automated measurement of crystal size has been developed. The main problem of crystals size measurements using image processing is the lack of an efficient algorithm to identify and separate overlapping and touching crystals which otherwise compromise the accuracy of size measurement. This problem of overlapping and touching crystals was addressed in two ways. First, 5 algorithms which identify and separate overlapping and touching crystals, using mathematical morphology as a tool, were evaluated. The accuracy of the algorithms depends on the technique used to mark every crystal in the image. Secondly, another algorithm which used convexity measures of the crystals based on area and perimeter, to identify and reject overlapping and touching crystals, have been developed. Finally, the two crystal sizing algorithms, the one applies ultimate erosion followed by a distance transformation and the second uses convexity measures to identify overlapping crystals, were compared with well established mechanical sieving technique. Using samples obtained from a sugar refinery, the parameters of interest, including mean aperture (MA) and coefficient of variance (CV), were calculated and compared with those obtained from the sieving method. The imaging technique is faster, more reliable than sieving and can be used to measure the full crystal size distributions of both massecuite and dry product.
dc.subjectSugar--Digital image processing.en_US
dc.titleSugar crystal size characterization using digital image processing.en_US


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