Food density estimation using fuzzy logic inference

This paper presents a novel application of fuzzy logic inference to food density estimation to support research in nutrition science. French fries are taken as an example of this new application. A fuzzy Inference System (FIS) is constructed to estimate the bulk density of French fries under differe...

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Bibliographic Details
Published inProceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference (NEBEC) pp. 1 - 2
Main Authors Chengliu Li, Fernstrom, John D, Sclabassi, Robert J, Fernstrom, Madelyn H, Wenyan Jia, Mingui Sun
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2010
Subjects
Application software
Cellular phones
Digital cameras
Fuzzy logic
Fuzzy sets
Fuzzy systems
Genetic algorithms
Temperature
Volume measurement
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Summary:This paper presents a novel application of fuzzy logic inference to food density estimation to support research in nutrition science. French fries are taken as an example of this new application. A fuzzy Inference System (FIS) is constructed to estimate the bulk density of French fries under different cooking conditions. Our experimental results show that our density estimation method is accurate with a mean error of 2.2%.
ISBN:9781424468799
1424468795
ISSN:2160-6986
2160-7028
DOI:10.1109/NEBC.2010.5458195