Saranya, P. and Durga, R. (2023) Food Safety Control Using CNN Model in Image Processing Technique. In: 2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS), Bangalore, India.
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Food Safety Control Using CNN Model in Image Processing Technique _ IEEE Conference Publication _ IEEE Xplore.pdf
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Abstract
Adulteration is one of the major problems in food products. It makes the food products impure and alters their original form. Food adulteration lowers the food’s quality by introducing adulterants or deleting necessary ingredients. Adding contaminants to the pure form of food is becoming a common practice to boost market growth. Some of the important food products that we consume daily such as fruits and vegetables have been adulterated with chemicals which cause harmful to health and cause various diseases. This research paper focuses on the overview of image processing techniques with CNN Models to detect adulteration from sample images of food products that we consume in our daily life. The images of food products such as cashew nuts, Rice grains, Corn seeds, green coffee beans, virgin olive oil are taken in some of the paper and various image processing techniques with convolution neural network algorithms are used to detect the adulterant mixed in the products from this the research paper gives an overall view of food adulteration with image processing and CNN models and its applications.
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Computer Science > Computer Networks |
Divisions: | Computer Science |
Depositing User: | Mr IR Admin |
Date Deposited: | 19 Sep 2024 10:52 |
Last Modified: | 19 Sep 2024 10:52 |
URI: | https://ir.vistas.ac.in/id/eprint/6547 |