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Classification of fruits using Probabilistic Neural Networks - Improvement using color features

This paper presents a novel approach for the development of an intelligent fruit sorting system using techniques from Digital Image Processing and Artificial Neural Networks. The aim is to develop a fast and effective classification method along with a target of 100% efficiency. Five fruits; i.e., a...

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Bibliographic Details
Main Authors: Mustafa N.B.A., Arumugam K., Ahmed S.K., Sharrif Z.A.Md.
Other Authors: 57191952020
Format: Conference Paper
Published: 2023
Subjects:
Colour Recognition
Fruit Classification
HSI
Morphological Feature Analysis
PNN
RGB
Color
Feature extraction
Image processing
Neural networks
Classification methods
Color features
Fruit sorting
MATLAB/Simulink environment
Morphological features
Probabilistic neural networks
Fruits
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Summary:This paper presents a novel approach for the development of an intelligent fruit sorting system using techniques from Digital Image Processing and Artificial Neural Networks. The aim is to develop a fast and effective classification method along with a target of 100% efficiency. Five fruits; i.e., apples, bananas, carrots, mangoes and oranges were analysed and seventeen features were extracted based on the fruits' morphological and colour characteristics. A regular digital camera was used to acquire the images, and all manipulations were performed in a MATLAB/SIMULINK environment. The results obtained were a significant improvement over a previous study. � 2011 IEEE.

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