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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 4, APRIL 2024

Fruit Quality Detection

Benoy Baby, Abhinav S Kumar, G S Devadath, Rahul S Renjith

DOI: 10.17148/IJARCCE.2024.134179

Abstract: One of the important quality features of fruits is its appearance. Appearance not only influences their market value, the preferences, and the choice of the consumer, but also their internal quality to a certain extent. Our project presents a Computer Vision based technology for fruit quality detection. This will be implemented in python using CNN. In this project, we will use an external web cam to capture the real time image of a given fruit. This web cam will be connected to a computer device. Using our software, it will analyze the given fruit and checks whether it has any abnormalities like black or brown spots or uneven texture. These indications help us to identify the quality of the given fruit. The use of this technology can significantly improve agriculture & fruit industry as well as computer vision systems provide rapid, economic, hygienic, consistent, and objective assessment which provides people with a healthier lifestyle.

Keywords: CNN

How to Cite:

[1] Benoy Baby, Abhinav S Kumar, G S Devadath, Rahul S Renjith, “Fruit Quality Detection,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.134179