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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| 主要な著者: | , , , |
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| フォーマット: | Conference Paper |
| 言語: | English |
| 出版事項: |
2017
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| タグ: |
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| 要約: | 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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