relation: https://khub.utp.edu.my/scholars/17266/
title: Detection of Insect Invasion Symptoms on Tree Leaves Using Image Processing
creator: Nordin, M.B.
creator: Hisham, S.B.B.
description: 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.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2022
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Nordin, M.B. and Hisham, S.B.B.  (2022) Detection of Insect Invasion Symptoms on Tree Leaves Using Image Processing.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148476989&doi=10.1109%2fICOCO56118.2022.10031739&partnerID=40&md5=0ef62535c91f585c163d1d9be9a3bcc3
relation: 10.1109/ICOCO56118.2022.10031739
identifier: 10.1109/ICOCO56118.2022.10031739