INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
One of the most critical aspects of quality assurance is inspecting products for defects before they are
sold or shipped. A good product is more vital than having more of the same item for a customer’s
enjoyment. the client has a significant role in determining the quality of a product. Another way to
think about quality is as the total of all the characteristics that contribute to the creation of items that
the client enjoys. Recently, the application of machine vision and image processing technology to
improve the surface quality of foods has increased significantly. this is primarily because these
technologies make significant advancements in areas where the human eye falls short. this means
that, by utilizing computer vision and image processing techniques, time-consuming and subjective
industrial quality control processes can be eliminated. Its excess food we waste has a large impact on
various environmental factors. This research paper discusses how to check and assess food using
picture segmentation and machine learning. then, we propose the development of a user-friendly
mobile application that allows customers to conveniently capture and analyse images of their ordered
food items in real-time. This application provides instant feedback on the freshness status of the food,
enabling customers to take proactive measures if any concerns arise. Segmentation of the image is
carried out using the K-means clustering technique. These algorithms determine if a food is fress or
not. Finally, freshness detection is carried out using the Machine learning algorithm. An application
is proposed to display the results of checking food items by the device.
"Smart Food Quality detection using ML", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.e151-e154, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403421.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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