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YADAV, A DUTTA, M. K. BURGET, R.
Original Title
Automated Visible Range Imaging Scheme to Identify Toxic Substance from Common Starchy Food
Type
conference paper
Language
English
Original Abstract
Toxic substance like acrylamide is a carcinogenic compound which is generally formed in the starchy food item when heated or fried to high temperatures. In the proposed work, a computer vision technique is employed to ascertain the presence of the acrylamide in the fried potato chips. K-means clustering has been used to perform a colour based segmentation of chips pixels from background. Distinct features, like standard deviation and moment,extracted from multi-channels, are fed to a random forest classifier for proper discrimination between acrylamide content potato chips samples and normal potato chips samples.Performance of the developed algorithm is evaluated on the comprehensive database of 80 sample images of the fried potato chips. The accuracy to detect the acrylamide contained potato chips is 95.83% which encourage the use of the proposed algorithm in real time application.
Keywords
image processing, artificial intelligence, machine learning
Authors
YADAV, A; DUTTA, M. K.; BURGET, R.
Released
27. 10. 2018
Publisher
2018 4th International Conference on Computational Intelligence & Communication Technology (CICT)
Location
Ghaziabad, India
ISBN
978-1-5386-0886-9
Book
International Conference on Computational Intelligence & Communication Technology (CICT)
Edition
4th
Pages from
1
Pages to
6
Pages count
URL
https://ieeexplore.ieee.org/document/8480363
BibTex
@inproceedings{BUT150882, author="YADAV, A and DUTTA, M. K. and BURGET, R.", title="Automated Visible Range Imaging Scheme to Identify Toxic Substance from Common Starchy Food", booktitle="International Conference on Computational Intelligence & Communication Technology (CICT)", year="2018", series="4th", pages="1--6", publisher="2018 4th International Conference on Computational Intelligence & Communication Technology (CICT)", address="Ghaziabad, India", doi="10.1109/CIACT.2018.8480363", isbn="978-1-5386-0886-9", url="https://ieeexplore.ieee.org/document/8480363" }