@inproceedings{7c610cec2e594e619fa5b8ac6ee89117,
title = "Towards Palm Bunch Ripeness Classification Using Colour and Canny Edge Detection",
abstract = "The ripeness of the farm-able palm fruits is an important factor in the production of quality palm oil. The work presented is an image processing implementation in the palm oil industry to eliminate human errors in the judgment of the ripeness of palm fruit bunches as well as to introduce automation. Various techniques were employed to obtain data from the images provided for the data mining process. The features used are the colour of the palm fruit bunches and the amount of edges representing visible leaves in the palm fruit bunches, indicating empty sockets. The project is able to achieve an accuracy of up to 79.11%.",
keywords = "Canny edge, Colour detection, Empty sockets, Palm kernel, Ripeness",
author = "Tan, {Ian K. T.} and Lim, {Yue Hng} and Hon, {Nyen Ho}",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 7th International Conference on Computational Science and Technology 2020, ICCST 2020 ; Conference date: 29-08-2020 Through 30-08-2020",
year = "2021",
doi = "10.1007/978-981-33-4069-5_4",
language = "English",
isbn = "9789813340688",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer",
pages = "41--50",
editor = "Rayner Alfred and Hiroyuki Iida and Haviluddin Haviluddin and Patricia Anthony",
booktitle = "Computational Science and Technology",
}