Automated Visible Range Imaging Scheme to Identify Toxic Substance from Common Starchy Food

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU129519" target="_blank" >RIV/00216305:26220/18:PU129519 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8480363" target="_blank" >https://ieeexplore.ieee.org/document/8480363</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CIACT.2018.8480363" target="_blank" >10.1109/CIACT.2018.8480363</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automated Visible Range Imaging Scheme to Identify Toxic Substance from Common Starchy Food

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Automated Visible Range Imaging Scheme to Identify Toxic Substance from Common Starchy Food

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

International Conference on Computational Intelligence & Communication Technology (CICT)

ISBN

978-1-5386-0886-9

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

2018 4th International Conference on Computational Intelligence & Communication Technology (CICT)

Místo vydání

Ghaziabad, India

Místo konání akce

San Carlos

Datum konání akce

18. 7. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000450112300038