تازه های تحقیق
عنوان مقاله [English]
Sieve test is a standard method widely used in sugar factories to determine the size of sugar particles. Needing for relatively large samples, time-consuming, limited measured parameters, being not automatic and offline are main disadvantages of the sieve test. Image processing technique can determine the parameters related to size and shape of sugar particles, quickly, automatically and instantly and is a good alternative to the sieve test. The objective of this study was presenting a suitable image processing algorithm for online determination of white sugar crystals size. First, the sugar mass crystals were sorted according to size using the standard sieve test (with 7 sieves at 10 replications). Then, the crystals images were taken by a digital microscope with 5 megapixels image sensor. Three marking methods, including foreground-background (FB), ultimate erosion (UE) and distance transform (DT), were used for images segmentation and determination of the crystals morphological parameters in the image processing toolbox of MATLAB software. The analysis of variance of mean aperture (MA) values was performed based on factorial experiment in a completely randomized design and the mean of MA values was compared with Duncan's multiple range test. The effects of both sieve size and segmentation method factors as well as their interaction on the MA value were significant. The MA of FB and UE markers were not significantly different from the reference MA value that obtained manually at 1% level. Since, the UE marker showed the best performance in MA determination due to a lower error (equal 10.13%), so it is recommended for online determination of white sugar particles size by image processing.