Cereal Grain Classification by Optimal Features and Intelligent Classifiers

Ali Douik, Mehrez Abdellaoui

Abstract


The present paper focused on the classification of cereal grains using different classifiers combined to morphological, colour and wavelet features. The grain types used in this study were Hard Wheat, Tender Wheat and Barley. Different types of features (morphological, colour and wavelet) were extracted from colour images using different approaches. They were applied to different classification methods.

Keywords


morphological, colour, wavelet transform, neural networks, statistical classifier, fuzzy logic

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References


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DOI: https://doi.org/10.15837/ijccc.2010.4.2508



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