Home
  • English
  • ÄŒeÅ¡tina
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • LatvieÅ¡u
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Log In
    Have you forgotten your password?
Home
  • Browse Our Collections
  • Publications
  • Researchers
  • Research Data
  • Institutions
  • Statistics
    • English
    • ÄŒeÅ¡tina
    • Deutsch
    • Español
    • Français
    • Gàidhlig
    • LatvieÅ¡u
    • Magyar
    • Nederlands
    • Português
    • Português do Brasil
    • Suomi
    • Log In
      Have you forgotten your password?
  1. Home
  2. Resources
  3. UniMAP Index Publications
  4. Publications 2021
  5. Automatic Counting of Palm Oil Tree Using Satellite Aerial Imagery
 
Options

Automatic Counting of Palm Oil Tree Using Satellite Aerial Imagery

Journal
Lecture Notes in Mechanical Engineering
ISSN
21954356
Date Issued
2021-01-01
Author(s)
Mohd Saifizi Saidon
Universiti Malaysia Perlis
Izzat M.A.
Wan Azani Wan Mustafa
Universiti Malaysia Perlis
DOI
10.1007/978-981-16-0866-7_5
Handle (URI)
https://hdl.handle.net/20.500.14170/5156
Abstract
Palm oil is an important economic crop in Malaysia and other tropical areas. The amount of palm oil in a plantation area is critical to forecast the yield of palm oil, to track and improve the productivity of palm-trees. The conventional manual counting approach is an unreliable result. So many processes are needed to pass and to document the outcome take a lot of time. In specific agricultural areas, palm tree counting is a crucial problem. A satellite (Google Earth Pro) has been used to gather data. The technique for the processing of images is identified and will detect and segment palm tree counts. Palm oil can be properly detected by counting palm oil based on this method in this study area. The image is processed in various techniques such as Gaussian filtering, sectional division and the unwanted object is removed. This enables a realistic, viable and effective image processing technique to calculate the average palm tree number with 94%.
Subjects
  • Counting system | Ima...

File(s)
research repository notification.pdf (4.4 MB)
Views
1
Acquisition Date
Nov 19, 2024
View Details
google-scholar
Downloads
  • About Us
  • Contact Us
  • Policies