• DocumentCode
    2273580
  • Title

    Food density estimation using fuzzy logic inference

  • Author

    Li, Chengliu ; Fernstrom, John D. ; Sclabassi, Robert J. ; Fernstrom, Madelyn H. ; Jia, Wenyan ; Sun, Mingui

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Pittsburgh, Pittsburgh, PA, USA
  • fYear
    2010
  • fDate
    26-28 March 2010
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    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%.
  • Keywords
    biomedical measurement; food products; fuzzy logic; medical computing; cooking conditions; density estimation method; food density estimation; french fries bulk density; fuzzy logic inference; nutrition science; Application software; Cellular phones; Databases; Digital cameras; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Temperature; Volume measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioengineering Conference, Proceedings of the 2010 IEEE 36th Annual Northeast
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4244-6879-9
  • Type

    conf

  • DOI
    10.1109/NEBC.2010.5458195
  • Filename
    5458195