Application Of Computer Vision Detection Of Apples And Oranges Using Python Language

  • Normalisa Normalisa Universitas Lintas Internasional Indonesia
  • Ani Rachmaniar STMIK Jakarta STI&K
  • Desi Diana STMIK Jakarta STI&K
  • Mohamad Saefudin STMIK Jakarta STI&K
  • Robin Parulian STMIK Jakarta STI&K

Abstract

The Indonesian nation, which is quite large, has the natural resources and potential manpower needed to build the archipelago's fruit industry. The climate and good weather cause Indonesia to have various types of fruits. Production of fruit crops in Indonesia in 2021 based on the website of the Central Statistics Agency, Indonesia produces millions of tons of fruit in total. In the fruit production processing industry, the quality of each fruit is generally checked, whether it is feasible to proceed to the processing stage or not. This check is carried out by employees manually without the help of tools. Sophisticated programs or systems can perform this task automatically. Artificial intelligence, which includes object recognition, has advanced as technology advances. It can identify items in an image. Object detection is one of the fields in computer vision. The use of computer vision technology allows machines to see and identify items in their environment similar to humans. By applying real-time object detection to an application, it can help sort out fruits that deserve to be processed in real-time through a camera that is installed in such a way. Based on the accuracy and the explanation result, the passing fruit will be detected automatically. The author uses a fruit image dataset with two object classes: fresh fruit and non-fresh fruit. The results obtained a high level of accuracy in the detection of apples and oranges.

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Published
2022-12-05
How to Cite
NORMALISA, Normalisa et al. Application Of Computer Vision Detection Of Apples And Oranges Using Python Language. Journal of Information System, Informatics and Computing, [S.l.], v. 6, n. 2, p. 455-466, dec. 2022. ISSN 2597-3673. Available at: <https://journal.stmikjayakarta.ac.id/index.php/jisicom/article/view/946>. Date accessed: 16 sep. 2024. doi: https://doi.org/10.52362/jisicom.v6i2.946.