In this study, three different apple varieties grown in Karaman province
are classified using kNN and MLP algorithms. 90 apples in total, 30 Golden
Delicious, 30 Granny Smith and 30 Starking Delicious have been used in the
study. DFK 23U445 USB 3.0 (with Fujinon C Mount Lens) industrial camera has
been used to capture apple images. 4 size properties (diameter, area, perimeter
and fullness) and 3 color properties (red, green, blue) have been decided using
image processing techniques through analyzing each apple image. A data set which contains 7 physical features
for each apple has been obtained. Classification success rates and error rates
have been decided changing the neuron numbers in the hidden layers in the classification
using MLP model and in different neighbor values in the classification made
using kNN algorithm. It is seen that the classification using MLP model is much
higher. While the success rate of classification made according to apple type
is 98.8889%.
Konular | Mühendislik |
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Bölüm | Research Article |
Yazarlar | |
Yayımlanma Tarihi | 26 Aralık 2016 |
Yayımlandığı Sayı | Yıl 2016 Cilt: 4 Sayı: Special Issue-1 |