Different Apple Varieties Classification Using kNN and MLP Algorithms
DOI:
https://doi.org/10.18201/ijisae.2016Special%20Issue-146967Keywords:
Image processing, Apple classification, kNN, MLPAbstract
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%.Downloads
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