editedbook
Publication: IIP Proceedings Year: 2022, Month: November Page No: 169-175, ISSN/ISBN: 978-93-95632-69-0, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl20234052E5A35710E68.pdf
GRADING OF PROCESSED ARECANUT USING MACHINE LEARNING
Area/Stream: IOT, Authors: Sakshi T, Rachitha M, Ashwathnarayan, Rachana S B Keywords: Grading, Process coconut Book Name /series: Futuristic Trends in IOT, Volume 2, Book 15, Part 4, Chapter 1Publication: IIP Proceedings Year: 2022, Month: November Page No: 169-175, ISSN/ISBN: 978-93-95632-69-0, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl20234052E5A35710E68.pdf
Abstract:
This system's major goal is to come up with a way to anticipate the various grades of arecanut based on their color, size, and texture. Several Indian states regularly cultivate arecanut, also known as betelnut. Most farmers now use human labour for sorting and Arecanut quality grading, which takes a lot of time and requires a lot of labour, leads to categorization irregularity. Since no tools or cutting-edge technologies are available. The creation of machine vision-based technologies could be useful for arecanut grading a benefit for farmers and assistance to society. Color, size, and shape are used to characterize the arecanuts carefully evaluated according to texture. These factors have a significant impact on how customers shop. For the quality grading of several categories of arecanut, image processing and machine vision have been utilized to extract exterior attributes like color, size, form, etc.
Cite this: Sakshi T, Rachitha M, Ashwathnarayan, Rachana S B,"GRADING OF PROCESSED ARECANUT USING MACHINE LEARNING", Futuristic Trends in IOT, Volume 2, Book 15, Part 4, Chapter 1, November, 2022, 169-175, 978-93-95632-69-0, https://www.rsquarel.org/assets/docupload/rsl20234052E5A35710E68.pdf
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