Disease Detection in Apple Leaves Using Image Processing Techniques


  • S. Alqethami College of Computer and Information Systems, Umm Al-Qura University, Saudi Arabia
  • B. Almtanni College of Computer and Information Systems, Umm Al-Qura University, Saudi Arabia
  • W. Alzhrani College of Computer and Information Systems, Umm Al-Qura University, Saudi Arabia
  • M. Alghamdi College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia


The agricultural sector in Saudi Arabia constitutes an essential pillar of the national economy and food security. Crop diseases are a major problem of the agricultural sector and greatly affect the development of the economies in various countries around the world. This study employed three prediction models, namely CNN, SVM, and KNN, with different image processing methods to detect and classify apple plant leaves as healthy or diseased. These models were evaluated using the Kaggle New Plant Diseases database. This study aims to help farmers detect and prevent diseases from spreading. The proposed method provides recommendations for the appropriate solutions for each type of recognized plant disease based on the classification results.


Machine learning, Disease of Plant, Apple, Deep learning


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How to Cite

S. Alqethami, B. Almtanni, W. Alzhrani, and M. Alghamdi, “Disease Detection in Apple Leaves Using Image Processing Techniques”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 2, pp. 8335–8341, Apr. 2022.


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