Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022

Edge Detection Of Potato Leaf Damage With Laplacian Of Gaussian Algorithm

Harahap, Mawaddah (Unknown)
Wijaya, Adrian Christian (Unknown)
Pasaribu, Samuel Henock Hasangapon (Unknown)
Sembiring, Giovan (Unknown)
Ginting, Kenjiro Christian (Unknown)



Article Info

Publish Date
01 Aug 2022

Abstract

The Potato plants are type young plant that easily attacked by pests and diseases, part of plant that often attacked by disease is leaves which can affect growth process and reduce crop yields. One way to determine if potato leaf is healthy or unhealthy is by using the edge detection method. Crop failure in potato plants can be detected through damage to leaves. The purpose of this study was to help facilitate identification type of damage to leaf margins of potato plants by applying the Laplacian of Gaussian algorithm. Based on results of testing on several research datasets sourced from the Agricultural Sector of the Karo Regency Government through an application of edge image detection on potato plant leaves through a grayscale, threshold and detection process with the Laplacian of Gaussian algorithm. It takes the longest time of 12.34 s with an error of 1.45 on the type of damage caused by aphids and at least 6.03 s with an error of 0.71 on the normal leaf edge detection results. Based on test results on 17 potato leaf images, the average test time is 8.45 s

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Journal Info

Abbrev

sinkron

Publisher

Subject

Computer Science & IT

Description

Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial ...