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need to train very
large or very small broccoli heads in which
case the error rate would increase since
leaves or weeds may be detected.
With harvesting systems such as this, fast
image processing times are required since
classification needs to be performed quickly.
On a tractor, for example, if the operator is
not driving in a perfectly straight line, the
camera will identify the broccoli head in a
certain position, but, by the time the robot
head reaches the broccoli head, the picking
arm could be out of position.
Using 2D image processing algorithms,
the broccoli heads can be identified and
then 3D algorithms can identify the center
of the broccoli head. To identify these
heads, deep learning techniques are applied
using the Polimago pattern matching tool,
part of the Common Vision Blox (CVB) soft-
ware from Stemmer Imaging (Puchheim,
Typically, working with organic products
such as broccoli is difficult. With computer
vision, many different variables must be
trained into the system, e.g. broccoli heads
that are very large or small with different
shape and texture.
Since each broccoli head looks slightly
different, the system needs to be trained
to identify whether they are perfectly circular or slightly miss-shaped. One of the
biggest challenges in such image identification is separating the broccoli head from
the leaf since the leaf will often blend into
the broccoli head. Thus, many different
images must be used to train the system,
a process that involves driving the tractor-based system around the field to identify
different types of broccoli heads as they
Once the system has identified the broc-
coli head, it needs to be graded by size.
Unfortunately, this is not an easy task since
the broccoli head may be partially covered
by leaves so that the leaves need to be seg-
mented from the broccoli heads. Using the
3D images, segmentation by texture can
separate the leaf from the broccoli heads.
The result is an image that contains only
data about the broccoli heads so that a mea-
surement of the diameter of the head can be
Using a graphical user interface (GUI) on
the PC, the operator can then select which
size of broccoli head is picked. After the
broccoli heads are correctly identified, their
positional information is sent from the trac-
tor’s on-board PC to a robot from Fanuc
(Oshino, Japan; www.fanuc.com) fitted with
a custom-built picking head. Those that are
not picked can then be identified and logged
for later analysis.
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