Harumanis mango leaf disease detection system using image processing technique / Nurhumaira Mohd Yusoff

Mohd Yusoff, Nurhumaira (2021) Harumanis mango leaf disease detection system using image processing technique / Nurhumaira Mohd Yusoff. Degree thesis, Universiti Teknologi MARA, Perlis.


Current Harumanis mango farming technique in Malaysia still mostly depends on the farmers’ own expertise to monitor the crops from the attack of pests and insects. This approach is susceptible to human errors and those who do not possess this skill may not be able to detect the disease at the right time. As leaf diseases seriously affect the growth of the crop and the quality of the yield, this project aims to develop a Harumanis Mango Leaf Disease Detection System (HLDDS) that detects the presence of disease in the mango leaf using image processing technique. First, the image is acquired through a smart phone camera, once it has been pre-processed, the image is then segmented in which the RGB image is converted to HSI image, then the features are extracted. Lastly, classification of disease is done to determine the type of leaf disease. The proposed system effectively detects and classify the disease with an accuracy of 68.89%. The findings of this project will contribute to the benefit of farmers and society and researchers can use the approach to address similar issues in future works.


Item Type: Thesis (Degree)
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Mohd Yusoff, Nurhumaira
Subjects: T Technology > T Technology (General) > Information technology. Information systems
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Pattern recognition systems
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Programme: Information Technology
Keywords: Harumanis Mango ; Leaf Disease ; Detection System ; Image Processing Technique
Date: 2021
URI: https://ir.uitm.edu.my/id/eprint/46029
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