Oil Plam Fruit Classification Using Spectrometer.
Artificial neural network and linear discriminant analysis were used to detect the ripeness of oil palm fruit bunches. The proposed classification scheme categorized the oil palm fruits into three classes, namely, overripe, ripe, and under-ripe. Fruit color, presumed to be an important indicator of...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/28408/1/Oil%20Plam%20Fruit%20Classification%20Using%20Spectrometer.pdf http://psasir.upm.edu.my/id/eprint/28408/ |
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| Institution: | Universiti Putra Malaysia |
| Language: | English English |
| Summary: | Artificial neural network and linear discriminant analysis were used to detect the ripeness of oil palm fruit bunches. The proposed classification scheme categorized the oil palm fruits into three classes, namely, overripe, ripe, and under-ripe. Fruit color, presumed to be an important indicator of the ripeness of oil palm fruits, was measured with the aid of a FieldSpec 3 Hi-Res spectroradiometer in the wavelength range of 400 nm to 1000 nm. The results were then compared with the classifications made by a trained human grader. |
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