Detection of Insect Invasion Symptoms on Tree Leaves Using Image Processing

Nordin, M.B. and Hisham, S.B.B. (2022) Detection of Insect Invasion Symptoms on Tree Leaves Using Image Processing. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

This project aims to help farmers in Lumut, Perak to combat thrips invasion on mango trees. It would help reduce loss of fruit-producing branches, manual inspections, and the need to cover large acres of land manually. Data was collected by using a Canon DSLR camera at lm distance in natural lighting and uncontrolled background. Images of healthy and diseased new leaves are pre-processed to remove noise. Masking and thresholding using a range of intensity values are used to remove the background. After that, the images were clustered using Fuzzy C-Means clustering. It was found that this method was more suitable than K-Means clustering as it uses a soft clustering approach. The images obtained were then classified using Support Vector Machine (SVM). An average classification accuracy of 9S.52 was achieved. © 2022 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 2022 IEEE International Conference on Computing, ICOCO 2022 ; Conference Date: 14 November 2022 Through 16 November 2022; Conference Code:186566
Uncontrolled Keywords: Fruits; Fuzzy logic; Image processing; Support vector machines, Fuzzy logic clustering; Images processing; Mango trees; Manual inspection; Natural lighting; Producing branches; REmove noise; Support vectors machine; Thrip invasion); Tree leaf, K-means clustering
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 19 Dec 2023 03:23
Last Modified: 19 Dec 2023 03:23
URI: https://khub.utp.edu.my/scholars/id/eprint/17266

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