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Weighing flowers as an alternative method for sorting by visual appearance
Year:
1996
Authors :
Lev, Munik
;
.
Zion, Boaz
;
.
Volume :
65
Co-Authors:
Zion, B., Inst. of Agricultural Engineering, Agricultural Research Organization, Volcani Center, P.O. Box 6, Bet Dagan, 50250, Israel
Lev, M., Inst. of Agricultural Engineering, Agricultural Research Organization, Volcani Center, P.O. Box 6, Bet Dagan, 50250, Israel
Facilitators :
From page:
325
To page:
334
(
Total pages:
10
)
Abstract:
The relationship between mass and visual appearance of flowers that are used as volume and background fillers in bouquets was studied. The main objective was to test whether weighing flowers could be used as a simple method for sorting, equivalent to doing so by their visual appearance, which is the combined impression made by a flower's dimensions, number of stems and leaves, and their density. Two methods of evaluating the visual appearance of flowers were used: (1) a qualitative and subjective method using an averaged decision made by a panel of human inspectors; (2) a quantitative and objective method using a computer vision system to acquire and analyse two video images of each flower, from perpendicular directions. It was found that human vision could clearly classify flowers as "small" or "big" according to their visual appearance. Classifying the flowers into two mass-classes ("light" and "heavy") closely matched the two-way human vision classification ("small" and "big"), based on the average decision of the panel of inspectors. On the basis of the averaged panel decisions, flowers of "light" and "heavy" classes looked more uniform when viewed separately than when viewed together. Flower mass correlated well with the average image area measured by the computer vision system. Based on these results it was concluded that the flowers studied could be classified by mass to achieve better uniformity of visual appearance. © 1996 Silsoe Research Institute.
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More details
DOI :
10.1006/jaer.1996.0106
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
29138
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:44
Scientific Publication
Weighing flowers as an alternative method for sorting by visual appearance
65
Zion, B., Inst. of Agricultural Engineering, Agricultural Research Organization, Volcani Center, P.O. Box 6, Bet Dagan, 50250, Israel
Lev, M., Inst. of Agricultural Engineering, Agricultural Research Organization, Volcani Center, P.O. Box 6, Bet Dagan, 50250, Israel
Weighing flowers as an alternative method for sorting by visual appearance
The relationship between mass and visual appearance of flowers that are used as volume and background fillers in bouquets was studied. The main objective was to test whether weighing flowers could be used as a simple method for sorting, equivalent to doing so by their visual appearance, which is the combined impression made by a flower's dimensions, number of stems and leaves, and their density. Two methods of evaluating the visual appearance of flowers were used: (1) a qualitative and subjective method using an averaged decision made by a panel of human inspectors; (2) a quantitative and objective method using a computer vision system to acquire and analyse two video images of each flower, from perpendicular directions. It was found that human vision could clearly classify flowers as "small" or "big" according to their visual appearance. Classifying the flowers into two mass-classes ("light" and "heavy") closely matched the two-way human vision classification ("small" and "big"), based on the average decision of the panel of inspectors. On the basis of the averaged panel decisions, flowers of "light" and "heavy" classes looked more uniform when viewed separately than when viewed together. Flower mass correlated well with the average image area measured by the computer vision system. Based on these results it was concluded that the flowers studied could be classified by mass to achieve better uniformity of visual appearance. © 1996 Silsoe Research Institute.
Scientific Publication
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