There are a growing demand and an urgent need for fruits due to the increase in the world population. Fruit diseases cause a devastating problem in production losses worldwide. The healthy recognition of fruits and apples is an important issue for the economic and agricultural fields. In this paper, a recognition system for apple fruit diseases detection is proposed and experimentally validated. The K-Means based segmentation technique is applied. In regards to performance enhancement, different features extraction techniques are applied and classified using Support Vector Machine, K-NN, Multi-Class Support Vector Machine, and Multi-Label KNN (ML-KNN). The proposed model can significantly support accurate detection and automatic classification of apple fruit diseases. The average accuracy of diseases classification is achieved up to 97.5% and up to 99% for apple health classification.
CITATION STYLE
Abd El-aziz, A. A., Darwish, A., Oliva, D., & Hassanien, A. E. (2020). Machine Learning for Apple Fruit Diseases Classification System. In Advances in Intelligent Systems and Computing (Vol. 1153 AISC, pp. 16–25). Springer. https://doi.org/10.1007/978-3-030-44289-7_2
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