Classification of Fruits Based on Shape and Color
using Combined Nearest Mean Classifiers

Classification of Fruits Based on Shape and Color
using Combined Nearest Mean Classifiers

fruit classification, nearest mean classifier, color features, shape features

Fruit classification is an important task in many agriculture industry. The fruit classification system can be used to identify the
types and prices of fruit. Manual classification of fruit is not efficient for large amount of fruits. The advancement of information
technology has made possible fruit classification be done by a machine. This research aims to propose a fruit classification
methodology based on shape and color. To reduce the effect of lighting variability a color normalization is carried out prior
to feature extraction. The color features used in this research are mean and standard deviation. The shape features are area,
perimeter, and compactness. The classification of an unknown fruit is carried out using the nearest mean classifier. The method
developed in this research is tested using 12 classes of fruits where each class is represented by a number of samples. The
experimental results show that the method proposed in this research provides an accuracy of 95.83% for two samples per class
and 100% for three samples per class. Experiment on small training samples has been conducted to evaluate the performance
of the proposed combined nearest mean classifiers and results obtained showed that the technique was able to provide good
accuracy

Abdullah1
, Agus Harjoko2
, Othman Mahmod3

Universitas Islam Indragiri Indonesia

02-02-2023

Fajar bagus W

PDF

Indonesia

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