Machine vision inspects fruit using off-the-shelf software
The MAF RODA system can perform optical sizing, color sorting, and detection of external defects on the fruit. The images are then processed using the Matrox MIL toolkit.
MAF Roda designs and manufactures several types of conveyor systems that use machine vision to support agriculture. These systems have one to ten parallel lanes and one to sixty four outlets that process different types of fruit ranging from cherry tomatoes to melons. The number of lanes determines the processing capacity of the machine--10 to 15vpieces of fruit per second, per lane--and the number of outlets defines the number of categories that the machine can sort.
One of these systems is the Globalscan, an automatic vision system that sorts fruit as it moves. The system allows packers to accurately grade fruit according to pre-established quality and color criteria to meet market requirements. Processing and packaging costs are reduced as substandard fruit is immediately removed from production batches.
The vision system includes proprietary double sensor CMOS high-resolution cameras (one color and one infrared camera per lane), acquisition boards, and LED lighting. Twenty color pictures and twenty infrared pictures are taken of each piece of fruit as it moves and rotates forward—covering 100 % of its surface.
The vision system can perform optical sizing (equatorial or maximum diameter, volume integration), color sorting (eight different criteria), and detection of external defects on the fruit. The images are then processed using the Matrox Imaging Library (MIL) toolkit.
Binarization and blob analysis are used to separate the fruit from its background and to obtain dimensions. The HLS (Hue, Luminosity, Saturation) color space conversion and statistical functions are used for color processing. And convolutions and custom-designed algorithms recognize stems and cores, and reject fruit with defects on the skin like black spots or russet.
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Posted by Vision Systems Design