Nordin, M.B. and Hisham, S.B.B. (2022) Detection of Insect Invasion Symptoms on Tree Leaves Using Image Processing. In: UNSPECIFIED.
Full text not available from this repository.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) |
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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 |