Tree Disease Detection System Using Artificial Intelligence

Lee, Chang Yi (2023) Tree Disease Detection System Using Artificial Intelligence. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

Plant disease has been affecting oil palm crop yield and traditional disease identification methods are ineffective and inconsistent. In order to detect disease based on image of the leaves, machine vision has been used in oil palm tree disease detection. There are many research attempts in assessing plant disease using machine learning and deep learning. However, the detection accuracy is low due to the extracted features lack sufficient discrimination. To solve this problem, an algorithm to detect the oil palm disease had been developed in this project. The proposed method consists of an image processing method and a machine learning technique for feature extraction and classification using MATLAB software. The highest testing accuracy obtained for industry dataset is 97.5% using SVM with linear kernel function, while public dataset got 96.1% using SVM with quadratic kernel function.