Image Based Oil Palm Tree Crowns Detection

• Main Author: Muhammad Afif Zakwan, Zaili
• Format: Final Year Project Report
• Language: English
• Published: Universiti Malaysia Sarawak (UNIMAS) 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/34377/2/Muhammad%20Afif%20Zakwan.pdf; http://ir.unimas.my/id/eprint/34377/

Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. This system is developed due to the ineffective traditional method, which are to manually identify and count, which takes a longer time and a lot of manpower. This system the main features is to detect the crowns of oil palm tree by drawing circle on it and covers the feature of counting for every single detection that has been made as an evaluation to ensure the system is completely done. This system adopting some features from existing work to identify the ideas and methods that indicate the exact position and detecting the oil palm tree crowns on the acquired images. The system initiates the process with changing the RGB image to Greyscale by using the CIE Lab Colour Space after inserting image. Otsu Threshold and Gaussian Filter is used to reduce the noise of the image by turn it to black and white. Canny edge segmentation algorithm is used after that to determine the edge of the crowns by differentiate the end of object and background. Centre of the edge is determined with Hough Transform and a dot is drawn on each centre followed by circle with fix radius set by the user. Once the circle is drawn, counting also take place simultaneously.