| Summary: | Harumanis
mango cultivar is special to Perlis (north state of Malaysia) and has been declared in the
national agenda as a special fruit.
For those who are not acquainted with aromatic mango, it
is difficult
to tell the distinction
between Harumanis and the others
.
By using image recognition, people can
identify
Harumanis feature details by image recognition technique where algorithm is applied to recognize the
mango.
Convolutional neural networks method is a suitable technique for the creation of a multi
-
fruit in
re
al
-
time classification sorter with the camera and for the detection of moving fruit. Furthermore, the
accuracy of the image classification can be improved by increasing the number of datasets, the distance
of images from the camera, and the labelling proce
ss.
This project
used
Mobile Net architecture model
because it consumes less computational power and it can
also
provide efficiency of the accuracy.
A
w
eb
-
based
i
mage
r
ecognition
s
ystem for
d
etecting Harumanis
m
angoes
was
developed and known as
CamPauh
to recognize four classes of mango which are
H
arumanis, apple mango, other
type
s
of
mango
es
and not mango.
CamPauh
ca
n
identify
different type of mangoes
and
the result
was
stored into
the database and
appeared
on the websit
e.
E
valuation
on the accuracy
was
conducted
discussed to
support users
’
satisfaction in identifying the correct mango type.
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