Machine-vision system helps classify fruit

MARCH 6--At the Institute of Agricultural Engineering, The Volcani Center (Bet-Dagan, Israel), Victor Alchanatis and his colleagues have developed a machine-vision system to examine the external features of tomatoes.

Mar 6th, 2002

MARCH 6--A number of companies use machine-vision systems to inspect the size, shape, color, and defects of fruit. At the Institute of Agricultural Engineering, The Volcani Center (Bet-Dagan, Israel), Victor Alchanatis and his colleagues have developed a machine-vision system to examine the external features of tomatoes. Designed to automatically inspect the fruit, the system uses three TK-1270 RGB color CCD cameras from JVC (Wayne, NJ) mounted on an arc surrounding the conveyor. According to Alchanatis, this setup provides a view from underneath the conveyor and two views from above. To digitize the color images, IVP-150 frame grabbers from BarGold (Haifa, Israel) deliver captured images into a PC-based system.

According to Alchanatis, the results obtained using the system showed good classification for color, color homogeneity, bruises, and stem detection. However, while shape results provided good detection of the tomato when it was placed properly, when placed incorrectly, the algorithm did not distinguish between the fruit and the cup in which the tomatoes were placed, providing erroneous results.

For more on this story, see Vision Systems Design, March 2002.

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