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Title: Classification of fruits using Probabilistic Neural Networks - Improvement using color features
Authors: Mustafa, N.B.A. 
Arumugam, K. 
Ahmed, S.K. 
Sharrif, Z.A.Md. 
Issue Date: 2011
Journal: IEEE Region 10 Annual International Conference, Proceedings/TENCON 2011, Article number 6129105, Pages 264-269 
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.
DOI: 10.1109/TENCON.2011.6129105
Appears in Collections:COE Scholarly Publication

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