ETHIOPIAN COFFEE BEAN DETECTION AND CLASSIFICATION USING DEEP LEARNING
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Date
2020-06-02
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Hawassa University
Abstract
Ethiopia is the homeland of Coffee Arabica. Coffee is the major commodity export which covers
the highest income source of foreign currency. In addition to this, Coffee has a great role in
social interaction between peoples and the source of income for the coffee-producing farmers.
Ethiopian coffee beans are distinct from each other in terms of quality based on their
geographical origins. Classification and grading of those coffee beans are based on growing
origin, altitude, bean shape and color, preparation method and others. However, the quality
of the coffee beans is determined by visual inspection, which is subjective, laborious, and prone
to error and this requires the development of an alternative method which is precise, non destructive and objective. Thus, the objective of this research is to design and develop a model
that characterizes and identifies coffee beans of six different origins of Ethiopia (Jimma,
Limmu, Nekemte, Yirgacheffe, Bebeka, and Sidama). Coffee beans for this research are
collected from the Ethiopian Coffee Quality Inspection and Auction Center (ECQIAC). Image
processing and the state-of-the-art deep-learning techniques were employed to automatically
classify coffee bean images into nine different class: washed Limmu, unwashed Limmu, washed
Sidamo, unwashed Sidamo, washed Yirgacheffe, unwashed Yirgacheffe, unwashed Jimma,
unwashed Nekemte, and washed Bebeka. A total of 9836 coffee bean images were used to train,
validate and test the CNN model. We have compared the classification result of the model
trained on different dataset sizes and hyperparameters. The model was trained on 80% of the
dataset, validated on 10%, and tested on 10% of the colorful coffee bean images, with batch
normalization has scored 99.89% overall classification accuracy and 0.92% generalization
log loss. In conclusion, the result of the study shows that CNN is an effective deep learning
technique in the classification of Ethiopian coffee beans
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Keywords
Ethiopian coffee, Coffee bean classification, Deep learning, CNN
