Mohd Saifizi Saidon
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Preferred name
Mohd Saifizi Saidon
Official Name
Mohd Saifizi , Saidon
Alternative Name
Saidon, Mohd Saifizi
Saifizi Saidon, M.
Saifizi, M.
Saidon, M. S.
Saifizi, Mohd
Main Affiliation
Scopus Author ID
56015096300
Researcher ID
AGY-2420-2022

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  • Publication
    Automatic Counting of Palm Oil Tree Using Satellite Aerial Imagery
    ( 2021-01-01)
    Mohd Saifizi Saidon
    ;
    Wan Azani Wan Mustafa
    ;
    Izzat M.A.
    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%.
  • Publication
    Automatic Counting of Palm Oil Tree Using Satellite Aerial Imagery
    ( 2021-01-01)
    Mohd Saifizi Saidon
    ;
    Izzat M.A.
    ;
    Wan Azani Wan Mustafa
    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%.