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Image analysis of pellet size for a control system in industrial feed production.

Ljungqvist MG, Nielsen ME, Ersbøll BK, Frosch S - PLoS ONE (2011)

Bottom Line: In this paper an image analysis method is proposed for automatic size-monitoring of pellets.This is called granulometry and the method used here is based on the mathematical morphological opening operation.In the proposed method, no image object segmentation is needed.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics and Mathematical Modelling, Technical University of Denmark, Kongens Lyngby, Denmark. malj@imm.dtu.dk

ABSTRACT
When producing aquaculture fish feed pellets, the size of the output product is of immense importance. As the production method cannot produce pellets of constant and uniform size using constant machine settings, there is a demand for size control. Fish fed with feed pellets of improper size are prone to not grow as expected, which is undesirable to the aquaculture industry. In this paper an image analysis method is proposed for automatic size-monitoring of pellets. This is called granulometry and the method used here is based on the mathematical morphological opening operation. In the proposed method, no image object segmentation is needed. The results show that it is possible to extract a general size distribution from an image of piled disordered pellets representing both length and diameter of the pellets in combination as an area.

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Size index comparison.The median of morphological opening intensity of dry pellets (blue) compared to the calliper diameter measurements of dry pellets (green), and their trend-lines, batch C. Size index values normalised for comparison purpose.
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pone-0026492-g018: Size index comparison.The median of morphological opening intensity of dry pellets (blue) compared to the calliper diameter measurements of dry pellets (green), and their trend-lines, batch C. Size index values normalised for comparison purpose.

Mentions: The opening intensity mean on dry pellets for batches C and D was compared to the calliper measurements’ mean area value. Since the opening operation measures both diameter and length of the pellets in an image, both are included as area in this correlation. The correlation of the two curves of batch C is 0.52, see Figure 18, and for Batch D the correlation is also 0.52. Moreover it can be seen that the trend-lines of the image analysis result correlate positively with the trend-lines of the calliper measurements’ mean value. For both batches C and D, the trend-lines of the image analysis and calliper measurements are increasing. An overview of the comparison between image analysis and calliper measurements can be seen in Table 2. For full results on correlation between image analysis and calliper measurements, see Table 3.


Image analysis of pellet size for a control system in industrial feed production.

Ljungqvist MG, Nielsen ME, Ersbøll BK, Frosch S - PLoS ONE (2011)

Size index comparison.The median of morphological opening intensity of dry pellets (blue) compared to the calliper diameter measurements of dry pellets (green), and their trend-lines, batch C. Size index values normalised for comparison purpose.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3198772&req=5

pone-0026492-g018: Size index comparison.The median of morphological opening intensity of dry pellets (blue) compared to the calliper diameter measurements of dry pellets (green), and their trend-lines, batch C. Size index values normalised for comparison purpose.
Mentions: The opening intensity mean on dry pellets for batches C and D was compared to the calliper measurements’ mean area value. Since the opening operation measures both diameter and length of the pellets in an image, both are included as area in this correlation. The correlation of the two curves of batch C is 0.52, see Figure 18, and for Batch D the correlation is also 0.52. Moreover it can be seen that the trend-lines of the image analysis result correlate positively with the trend-lines of the calliper measurements’ mean value. For both batches C and D, the trend-lines of the image analysis and calliper measurements are increasing. An overview of the comparison between image analysis and calliper measurements can be seen in Table 2. For full results on correlation between image analysis and calliper measurements, see Table 3.

Bottom Line: In this paper an image analysis method is proposed for automatic size-monitoring of pellets.This is called granulometry and the method used here is based on the mathematical morphological opening operation.In the proposed method, no image object segmentation is needed.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics and Mathematical Modelling, Technical University of Denmark, Kongens Lyngby, Denmark. malj@imm.dtu.dk

ABSTRACT
When producing aquaculture fish feed pellets, the size of the output product is of immense importance. As the production method cannot produce pellets of constant and uniform size using constant machine settings, there is a demand for size control. Fish fed with feed pellets of improper size are prone to not grow as expected, which is undesirable to the aquaculture industry. In this paper an image analysis method is proposed for automatic size-monitoring of pellets. This is called granulometry and the method used here is based on the mathematical morphological opening operation. In the proposed method, no image object segmentation is needed. The results show that it is possible to extract a general size distribution from an image of piled disordered pellets representing both length and diameter of the pellets in combination as an area.

Show MeSH