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DOI: 10.14569/IJACSA.2020.0110757
PDF

An Intelligent Approach for Detecting Palm Trees Diseases using Image Processing and Machine Learning

Author 1: Hazem Alaa
Author 2: Khaled Waleed
Author 3: Moataz Samir
Author 4: Mohamed Tarek
Author 5: Hager Sobeah
Author 6: Mustafa Abdul Salam

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.

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Abstract: Today’s palm trees diseases which cause a huge loss in production are extremely hard to detect either because these diseases are hidden inside the texture of the palm itself and cannot be seen by naked eyes or because it appears on its leaves which are hardly examined due to how far they really are from the ground. In this paper we’re interested in detecting three of the most common diseases threatening palms today, Leaf Spots, Blight Spots and Red Palm Weevil. Diagnosis of these diseases are done by capturing normal and thermal images of palm trees then, image processing techniques were applied to the acquired images. Two classifiers were used, CNN to differentiate between Leaf Spots and Blight Spots diseases and SVM for Red Palm Weevil pest. The results for CNN and SVM algorithms showed a success rate of accuracy ratio 97.9% and 92.8% respectively, these results are considered to be the best results in this domain as far as we know. The paper also includes the first gathered thermal images dataset for palms infected with Red Palm Weevil and healthy palms as well.

Keywords: Machine learning; deep learning; image processing; leaf spots; blight spots; red palm weevil

Hazem Alaa, Khaled Waleed, Moataz Samir, Mohamed Tarek, Hager Sobeah and Mustafa Abdul Salam, “An Intelligent Approach for Detecting Palm Trees Diseases using Image Processing and Machine Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110757

@article{Alaa2020,
title = {An Intelligent Approach for Detecting Palm Trees Diseases using Image Processing and Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110757},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110757},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Hazem Alaa and Khaled Waleed and Moataz Samir and Mohamed Tarek and Hager Sobeah and Mustafa Abdul Salam}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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