ABSTRACT

It's difficult to develop a fruit identification system that is dependable. Orchards exhibit a variety of complicated elements, including shifting light, change in appearance, and occlusion. Citrus fruit orchids are infamous for their difficulty in agriculture. Manual fruit counting has been attempted, however it is time consuming and labor intensive. The main aim of this paper is to minimize human-computer interactions, accelerate identification, and enhance the usability of the graphical user interface over current manual choices. This configuration utilizes a Raspberry Pi and a camera. This approach preprocesses images, extracts features, and classifies fruit using machine learning. This article covers how to count and distinguish tree fruits using computer vision and machine learning. Keywords: Fruit Detection, Fruit Classification, Computer Vision, Citrus fruit
Publication date: 01/12/2021

https://ijbpas.com/pdf/2021/December/MS_IJBPAS_2021_DEC_SPCL_2017.pdf

Download PDF
https://doi.org/10.31032/IJBPAS/2021/10.12.2017