Cereal Grain Classification by Optimal Features and Intelligent Classifiers

  • Ali Douik Ecole Nationale d’Ingénieurs de Monastir (ENIM) Département de Génie Electrique Laboratoire ATSI Rue Ibn El Jazzar, 5019 Monastir Tunisie
  • Mehrez Abdellaoui Ecole Nationale d’Ingénieurs de Monastir (ENIM) Département de Génie Electrique Laboratoire ATSI Rue Ibn El Jazzar, 5019 Monastir Tunisie

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.

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Published
2010-11-01
How to Cite
DOUIK, Ali; ABDELLAOUI, Mehrez. Cereal Grain Classification by Optimal Features and Intelligent Classifiers. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 5, n. 4, p. 506-516, nov. 2010. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/2508>. Date accessed: 06 aug. 2020. doi: https://doi.org/10.15837/ijccc.2010.4.2508.

Keywords

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