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

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Date
2011
Authors
Mustafa N.B.A.
Arumugam K.
Ahmed S.K.
Sharrif Z.A.Md.
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Research Projects
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Abstract
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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Keywords
Colour Recognition , Fruit Classification , HSI , Morphological Feature Analysis , PNN , RGB , Color , Feature extraction , Image processing , Neural networks , Classification methods , Color features , Fruit sorting , HSI , MATLAB/Simulink environment , Morphological features , PNN , Probabilistic neural networks , RGB , Fruits
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